MCP server

Valuein — SEC EDGAR Fundamentals & Smart-Money Data Official

io.github.valuein/mcp-sec-edgar

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Point-in-time, survivorship-free SEC EDGAR fundamentals + smart-money signals for AI agents.

Website Source

At a glance

Type

MCP server

Publisher

valuein.biz (verified by the MCP Registry)

Status

Working at last check

Tools

127

Token cost

About 71,861 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http mcp-sec-edgar https://mcp.valuein.biz/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.mcp-sec-edgar]
url = "https://mcp.valuein.biz/mcp"

Gemini CLI

{"mcpServers":{"mcp-sec-edgar":{"httpUrl":"https://mcp.valuein.biz/mcp"}}}

Cursor

{"mcpServers":{"mcp-sec-edgar":{"url":"https://mcp.valuein.biz/mcp"}}}

VS Code

{"servers":{"mcp-sec-edgar":{"type":"http","url":"https://mcp.valuein.biz/mcp"}}}

Antigravity

agy mcp add mcp-sec-edgar https://mcp.valuein.biz/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"mcp-sec-edgar","server_url":"https://mcp.valuein.biz/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"mcp-sec-edgar","server_url":"https://mcp.valuein.biz/mcp"}

Tools

• approve_staged_action ~383 tokens
  Approve a staged action by id and RUN the underlying tool call it proposed, using the caller's own current credentials — never the original proposer's. Idempotent and race-safe: an action already decided (approved by a concurrent call, rejected, executed, or failed) is NEVER re-executed — this retur
• cancel_scheduled_task ~213 tokens
  Cancel a pending scheduled task by id (from schedule_task or list_scheduled_tasks). Only a `pending` task can be cancelled — one that already woke (completed) cannot be un-woken. Idempotent: cancelling an already-cancelled task is a no-op. Undoable: `restore_deleted` with kind `scheduled_task` and t
• compare_periods ~506 tokens
  Compare a company's core financial metrics across two fiscal periods side-by-side. Shows absolute and percentage changes with significance classification (minor < 5%, notable 5–15%, significant > 15%). The response includes a `material_changes` count: this is the number of metrics whose `significanc
• compute_accretion_dilution ~865 tokens
  M&A accretion/dilution: the standard sell-side/banker quick-screen for whether a proposed acquisition adds to (accretive) or subtracts from (dilutive) the acquirer's EPS in the first pro-forma year. Pulls net income + shares outstanding for both companies, and each side's latest EOD close (acquirer'
• compute_dcf ~1296 tokens
  Forward discounted-cash-flow valuation (two-stage Gordon-growth model): caller provides growth + WACC + terminal assumptions, returns per-share intrinsic value (`value_per_share_cents`, cents USD) + 5×5 sensitivity grid. Pulls FCF base + net debt + shares from R2; caller can override any field. Defi
• compute_lbo ~959 tokens
  Leveraged buyout returns analysis: caller provides entry/exit multiples, leverage, and a hold period; the tool builds a Day-1 pro-forma opening balance sheet from the deal's own sources & uses (cash-free, debt-free convention — entry_debt = leverage_multiple x EBITDA, sponsor_equity = entry_enterpri
• create_report ~704 tokens
  Synchronously generate a research report and persist it under the caller's authorship. Two subtypes: • `reverse_dcf` — solves the stage-1 free-cash-flow growth rate the market price implies, with a 5×5 sensitivity grid across WACC × terminal-growth assumptions. Returns full markdown + structured JS
• create_rule ~2349 tokens
  Persist a trigger -> action rule and register it with the evaluator. 7 trigger types accepted (alert_fired, schedule_tick, inbox_item, price_threshold, filing_event, manual, scheduled_task_wake) x six action types (run_team, send_alert, create_report, score_thesis, schedule_task, post_inbox). These
• create_signal ~2520 tokens
  Persist a signal and register it with the firing pipeline. Five condition shapes: * `filing_event` — fire when a ticker files a chosen form type (8-K, 10-K, etc.). * `ratio_threshold` — fire when a ticker's financial ratio crosses a threshold (e.g. interest_coverage < 1.5). * `watchlist_change
• delete_agent Deletes data · ~210 tokens
  Delete one of the caller's own standing agents by id. Undoable: `restore_deleted` with kind `agent` and this agent_id brings it back as it was (enabled or paused). System agents (is_system:true on get_agent/list_agents — built-in agents the platform provisions) cannot be deleted and are rejected wit
• delete_agent_memory Deletes data · ~304 tokens
  Forget ONE durable memory entry by key — use it when a note you stored is now wrong, superseded, or was only ever scratch. Every entry is re-read into your context at the start of every future run, so leaving a stale one behind means re-grounding yourself in something false; deleting is the correcti
• delete_citation_override Deletes data · ~235 tokens
  Remove a user-authored citation correction by fact_id. Idempotent — deleting a missing override returns deleted=false without error. UNDOABLE: restore_deleted with kind 'citation_override' brings it back (unless a new save for the same fact_id replaced it). Once deleted, reports that previously rend
• delete_claim Deletes data · ~160 tokens
  Soft-delete a claim by id. The row and its score history are preserved for audit (archived, not erased); the claim drops out of default list_claims results. Idempotent — deleting an already-archived claim succeeds. Tier: all paid + free tiers (sample rejected).
• delete_figure_review Deletes data · ~236 tokens
  Remove your own review mark for ONE figure in a report (Undo for save_figure_review), so the figure needs review again. Keyed on (report_id, figure_key). Idempotent: `deleted` is false when no mark existed. Owner-scoped — only your own marks are reachable; a report you do not own simply has no mark
• delete_report Deletes data · ~164 tokens
  Soft-delete a report owned by the caller: status flips to `delisted`, visibility to `private` — not a hard delete, the row and R2 artifact are preserved (90-day audit window). Idempotent (deleting an already-delisted report succeeds). Sample tier rejected.
• delete_rule Deletes data · ~192 tokens
  Delete a rule by id (from create_rule/list_rules) — hides it from the catalog and removes it from the evaluator's scan index, so it stops firing immediately. UNDOABLE: restore_deleted with kind 'rule' brings it back and resumes evaluation (subject to the signal cap). Rules are immutable — to change
• delete_signal Deletes data · ~179 tokens
  Soft-delete a signal by its id (from create_signal/list_signals): status flips to `deleted` and it is removed from the cron evaluator index so it stops firing. Signals are immutable — to change one, delete then create_signal. Idempotent. Tier: sp500+ (sample rejected).
• delete_thesis Deletes data · ~197 tokens
  Soft-delete a saved thesis: status flips to `archived` (the row stays for audit / re-scoring). Idempotent — archiving an already-archived thesis succeeds. Hard-delete is not supported by design; future versions may expire archived theses after N years. This does not delete the claims linked to the t
• delete_uploaded_document Deletes data · ~169 tokens
  Delete an uploaded document before its 24h TTL. UNDOABLE: restore_deleted with kind 'uploaded_document' brings it back while it is still within its 24h TTL and its file exists. Deleting a missing/already-expired/foreign id returns deleted:false rather than an error.
• delete_watchlist Deletes data · ~166 tokens
  Soft-delete a watchlist by its name (not id): status flips to `archived` (still readable via list_watchlists status=all/archived). The name is freed for reuse by a new save_watchlist. Idempotent. Tier: sp500+ (sample rejected).
• describe_schema ~206 tokens
  Returns the Parquet schema for all tables in the Valuein SEC data warehouse. Includes table descriptions, column names, types, primary keys, and foreign-key references. Use this tool to understand the data model before querying with other tools. No data reads required — schema is embedded in the man
• dismiss_inbox_item ~195 tokens
  Soft-delete a single inbox item by its id (from list_signal_inbox) — not a signal id; sets `dismissed_at`. The row stays queryable via `list_signal_inbox(include_dismissed=true)` for audit. Undoable: `restore_deleted` with kind `inbox_item` and this inbox_id un-dismisses it. Idempotent. Tier: sp500+
• find_in_filing ~1268 tokens
  Find a statement, note, heading or phrase inside a 10-K / 10-Q (or amendment) and get where to read it, like grep over the filing: 'Consolidated Balance Sheets', 'goodwill impairment', 'Note 7', 'Risk Factors'. Searches the same text read_filing_section serves, so each hit's `key` and `offset` are t
• forensic_audit ~230 tokens
  Deterministic forensic-accounting scores for a single ticker: partial Beneish M-Score, Sloan accruals, and a solvency snapshot. Returns a red-flag narrative ranked by severity, with citations to source filings. Used by the `forensic_earnings_brief` SOP. Note: full Beneish needs AR / current assets
• generate_comps_xlsx ~734 tokens
  Render a peer comparables table into an Excel workbook. The Comps sheet is formatted as a named Excel Table (`ValueinPeerComps`) so the user gets one-click Insert Chart on any column — the cleanest workaround for not embedding chart objects server-side. Subject-row highlight makes side-by-side compa
• generate_dcf_xlsx ~774 tokens
  Render a forward DCF result into a professional Excel workbook (Summary + 5×5 Sensitivity heatmap + Inputs sheet). Native conditional formatting — no chart images needed. Returns a 15-minute presigned R2 download URL. SERVER-TRUST: the DCF is re-derived in-Worker from the supplied `inputs_echo` (th
• generate_lbo_xlsx ~1450 tokens
  Render an LBO result into a professional Excel workbook (Summary + year-by-year Projection table + Inputs sheet). Returns a 15-minute presigned R2 download URL. SERVER-TRUST: the deal is re-derived in-Worker from the supplied `lbo_result.inputs_echo` (the math is pure + deterministic) and the workb
• generate_research_brief_docx ~980 tokens
  Render a structured research brief into a professionally-styled Word document — a branded masthead-first page (Valuein letterhead: brand rule, wordmark, 'EQUITY RESEARCH' kicker + date, then the ticker eyebrow, the title as hero, and the named analyst's byline), the body (abstract, optional snapshot
• get_agent ~178 tokens
  Fetch full detail for one of the caller's own standing agents by id (from save_agent/list_agents). Returns `found: false` (not an error) for an unknown id OR an id belonging to another customer — there is no distinguishing signal, by design, matching get_agent_run's posture. Tier: sp500+ (sample rej
• get_agent_memory ~194 tokens
  Recall this user's durable memory. Omit `key` (or pass null) to read EVERYTHING you have remembered, newest-first — do this at the START of a task to re-ground yourself. Pass a specific `key` to fetch one entry. An absent key returns an empty list, never an error (absence is a first-class answer). T
• get_agent_run ~213 tokens
  Fetch full detail for one of the caller's own standing-agent runs by id (from list_agent_runs) — status, goal, tickers, cost, artifact ids, role breakdown, and any error. A run may have been triggered by this same agent or by the customer's own Workspace; this tool works either way. Returns `found:
• get_blockholders ~567 tokens
  Returns SC 13D / SC 13G blockholder disclosures (5%+ stakes) for a US public company. Each row carries percent_owned, sole/shared voting + dispositive split, schedule_type, and the first-class ``going_active`` flag — TRUE when the same filer flipped 13G → 13D within the lookback window (the single m
• get_capital_allocation_profile ~596 tokens
  Get a multi-year capital allocation breakdown for a US public company. Shows how management deploys cash across all six categories — capex, R&D, M&A, dividends, buybacks, and debt — plus pre-computed deployment ratios (% of operating cash flow) and over-distribution flags. Use this tool when the use
• get_claim ~159 tokens
  Fetch a single claim by id, plus the ids of theses it supports/refutes and its full append-only score history. Use this to inspect a claim's evidence, current status, and how its outcome has evolved. Tier: all paid + free tiers (sample rejected).
• get_company_fundamentals ~1301 tokens
  Retrieve standardized SEC EDGAR fundamental financial metrics for a US public company. Returns revenue, gross profit, operating income, net income, EPS (diluted), total assets, total liabilities, stockholders' equity, cash & equivalents, total debt, operating cash flow, and capital expenditures for
• get_compute_ready_stream ~442 tokens
  Returns a short-lived (15-min) download URL for a bulk Parquet object that can be piped directly into Python/DuckDB/Polars for high-throughput computation that exceeds the MCP context window. The URL streams the object straight from Valuein storage and supports HTTP range reads, so `duckdb.read_parq
• get_earnings_signals ~519 tokens
  Reported earnings results and a model-derived earnings-trend signal for a company, by fiscal period: actual reported EPS, a trailing-trend EPS estimate (`eps_trend_est`), the deviation of actual vs that trend (`eps_surprise_pct`), reported revenue, and year-over-year revenue growth. IMPORTANT: `eps_
• get_financial_ratios ~1126 tokens
  Get pipeline-computed financial ratios from ratio.parquet. Served categories: profitability (margins, ROE, ROA, ROIC), liquidity (current ratio, quick ratio), leverage (D/E, interest coverage, net debt/EBITDA), efficiency (asset turnover, inventory days), per_share (EPS, BVPS, FCF/share), owner_earn
• get_insider_sentiment ~315 tokens
  Role-weighted insider sentiment score on a fixed [-100, +100] scale for a single issuer over a lookback window. Role weights: CEO/CFO = 3.0 (via officer_title pattern), other NEO Officer = 2.0, 10%-Owner = 1.5, Director = 1.0. P = +1, S = -1; option exercises, grants, and tax withholdings are neut
• get_insider_transactions ~641 tokens
  Form 3 / 4 / 5 / 144 line items for a US public company. Returns each transaction (or initial holding / proposed sale) with the insider's name, role, transaction code, share count, price, and notional. Filters by lookback window, transaction code (P=purchase, S=sale, A=grant, M=option exercise, F=t
• get_institutional_holdings ~595 tokens
  Returns top-N institutional holders of a US public company at a specific period_end (latest by default), with aggregate institutional shares, total market value, holder count, and HHI concentration (sum of squared share-of-total percentages). Sourced from Form 13F-HR via the by-issuer partition. I
• get_manager_portfolio ~616 tokens
  Returns a 13F filer's full portfolio at a specific period_end (latest by default), with QoQ deltas vs the prior quarter (new / increased / decreased / exited / unchanged). Specify the filer either by filer_cik (preferred) or filer_name (fuzzy match against entity.name; multiple matches raise an amb
• get_morning_brief ~237 tokens
  Read the caller's Morning Brief — a daily AI-generated market digest covering overnight moves across the customer's own watchlists and theses, produced by the Workspace. Omit `day` to get the most recent brief available (not necessarily today's); pass a specific `day` (YYYY-MM-DD) to fetch that day'
• get_peer_comparables ~882 tokens
  Get ratio-based peer comparison for a company and its closest competitors. Peers are selected by matching 2-digit SIC industry code. Returns pipeline-computed ratios from up to 10 peers alongside the subject company for direct benchmarking. Ratio categories: profitability, liquidity, leverage, effic
• get_pit_universe ~1544 tokens
  Use this tool to answer questions about historical index membership — e.g. "Was Company X in the S&P 500 on date Y?" or "Which companies were in the Russell 2000 on 2010-01-01?" Use this INSTEAD OF `search_companies` when the question involves a specific historical date or whether a company was an i
• get_pit_valuation_ratios ~822 tokens
  Current and historical valuation multiples for a company. Omit `as_of_date` and it returns today's P/E, P/S, P/B, EV/EBITDA, EV/Revenue and FCF yield, computed from the latest EOD close and the latest TTM financials. Use it for any "what is X's P/E " / "how is X valued right now" question — never de
• get_price_history ~944 tokens
  Daily EOD bar series (OHLCV) for a company over a date range. Returns up to 252 trading-day bars oldest-first — one bar per trading day. Each bar carries: open / high / low / close (raw, unadjusted), total_return_index (dividends reinvested and splits neutralized, forward-compounded from an arbitrar
• get_report ~276 tokens
  Fetch the current HEAD of a report by id. `format=markdown` returns the rendered body, `format=json` returns the full structured payload (sections + citations + report-type-specific data), `format=preview` returns abstract-only. Authors see any of their own reports; non-authors only get `preview` of
• get_report_version ~255 tokens
  Author-only fetch of a specific archived version of one of your reports, by positive-integer `version`. Returns metadata + the full payload (sections, citations, structured, markdown) — enough to render a diff against the current HEAD in the workspace editor. Use after `list_report_versions` identif
• get_research_file ~816 tokens
  Fetch the Auditable Research File behind one of the caller's own agent runs — the complete evidence chain an examiner asks for: the originating prompt, every tool the agent called in order, every `fact_id` it cited, every human approval, and which models were used. Assembled from the immutable audit
• get_sec_filing_links ~761 tokens
  Get direct links to original SEC EDGAR filings for any US public company. Returns four per-filing deep links: `sec_url` (the EDGAR filing-index page listing every document), `viewer_url` (the cgi-bin Financial-Report viewer for the specific accession), `inline_viewer_url` (the SEC Inline-XBRL viewer
• get_smart_money_flow ~679 tokens
  Composite flow score on [-100, +100] aggregating insider transactions, 13F institutional Δ-shares vs the prior quarter, and SC 13D/13G blockholder changes over a lookback window. Each component normalised independently, then combined with configurable weights (default: institutional 0.4, blockholder
• get_sop ~387 tokens
  Load one expert research playbook by name (discover names with `list_sops`). Returns the full procedure: the ordered tool sequence, which calls to group into parallel waves, the provenance and citation rules, and the exact output structure. Supply the playbook's arguments (e.g. `ticker`) to get a c
• get_stock_price ~720 tokens
  End-of-day closing price for a company AS OF any calendar date. Pass `date` to get the close on that day; if the date falls on a weekend or market holiday, it resolves backward to the most recent prior trading day's close (the `price_date` field tells you which day was actually used, and `resolved_b
• get_thesis ~175 tokens
  Fetch a single saved thesis by its id. Returns the full record including outcome (if scored). Returns NOT_FOUND if the id is unknown or belongs to another user. For the claims composing a thesis use list_claims_for_thesis; for an individual claim use get_claim. Tier: paid + free (sample rejected).
• get_top_holders ~531 tokens
  Classification-aware UNION across insider transactions (latest post_transaction_shares per insider), 13F institutional holdings, and SC 13D / 13G blockholder filings for one issuer. Each row carries holder_class ∈ {insider, institutional, blockholder_13D, blockholder_13G}. Dedupes overlapping file
• get_uploaded_document ~177 tokens
  Read the extracted text of a file uploaded via POST /v1/uploads (a plain REST route, not this JSON-RPC endpoint). Use this to pull a user-attached document's content into context by its upload_id. Uploads are ephemeral (24h) and owner-scoped — an expired or missing id both read back as not-found.
• get_valuation_metrics ~710 tokens
  Get what a US public company is TRADING AT, plus two parameter-free reference points. This is NOT an opinion of intrinsic worth — for that, call `compute_dcf` with assumptions you state explicitly, and present the result as a scenario, never as "the" fair value. Returns per-period data combining com
• get_watchlist ~141 tokens
  Fetch a single watchlist (full ticker set + criteria) by its name, not an id (case-insensitive). NOT_FOUND if the name is unknown to this user. Tier: sp500+ (sample rejected).
• link_claim_to_thesis ~306 tokens
  Attach a claim to a thesis with a role: 'supports' (the claim, if true, strengthens the thesis), 'refutes' (if true, weakens it — track disconfirming evidence first-class), or 'context' (relevant but not directional). Idempotent — re-linking updates the role. A claim can support one thesis and refut
• list_agent_runs ~310 tokens
  List the caller's own standing-agent runs, newest first — status, goal, cost, and timing for each. A run may have been kicked off by this same agent (e.g. via create_rule's run_team action, a schedule_task wake, or run_agent) OR by the customer's own Workspace UI; this tool lets any MCP client check
• list_agents ~210 tokens
  List the caller's own standing agents (id, name, goal, tickers, agent_type, trigger config, schedule, enabled state, last/next run). Optionally filter by `agent_type` ("workflow" or "autonomous"). Use get_agent for one agent's full detail, list_agent_runs for run history, or run_agent to fire one no
• list_citation_overrides ~350 tokens
  Author-only newest-first listing of the caller's citation corrections. Filterable by ticker (e.g. all AAPL corrections) or by a single fact_id (returns 0 or 1 row). Pair with `save_citation_override` and `delete_citation_override`. Sample tier rejected. Agent use: call with `ticker` to introspect w
• list_claims ~429 tokens
  List the caller's saved claims, most-recent-first, with AND-composed filters and cursor pagination. Filter by ticker, claim_type (assertion/prediction/judgment), tag, or lifecycle status (open/confirmed/refuted/expired/stale/needs_review). Archived claims are excluded unless include_archived is set.
• list_claims_for_thesis ~172 tokens
  List the claims composing a thesis, each with its role (supports/refutes/context). This is how you read a thesis as the structured argument it is — its supporting and disconfirming claims with their current statuses. Archived claims are omitted. Tier: paid + free (sample rejected).
• list_figure_reviews ~196 tokens
  List every figure review recorded for one report, plus a state-count summary — the coverage view for 'which figures in this report still need a human?' A report with no reviews yet returns an empty list and an all-zero summary; that is a legitimate answer, not an error. Owner-scoped — only returns y
• list_filing_forms ~283 tokens
  Which SEC form types each of up to 200 companies filed in the last N months (default 24), as a count per form, in ONE call. Use it to offer only forms a company set actually files (10-K, 10-Q, 20-F, 40-F, 6-K, 8-K, DEF 14A, ...). Amendments count toward their base form (10-K/A is a 10-K). A company
• list_filing_sections ~679 tokens
  Table of contents of a 10-K / 10-Q (or 10-K/A, 10-Q/A) so an agent can read the filing's WORDS: returns the form, filing/period/acceptance dates, the primary-document URL, and every section found with its `key`, `title`, `char_count` and a short `first_line`. 10-K keys are the Item numbers (1, 1A, 1
• list_my_reports ~306 tokens
  Cursor-paginated newest-first listing of the caller's own reports (owner-scoped). Filters compose with AND; `status` defaults to 'ready' so pass status='draft' or 'all' to see drafts. Use `cursor` from the previous response's `next_cursor` to fetch the next page (limit max 100). Sample tier rejected
• list_pending_approvals ~188 tokens
  List the caller's own staged actions still awaiting a human decision (status='proposed'), newest-first. Use this to check what an autonomous run has queued up before you approve or reject it with `approve_staged_action` / `reject_staged_action`. Tier: sp500+ (sample rejected).
• list_public_claims_by_user ~257 tokens
  Return the PUBLIC claims + claim-accuracy reputation for a user identified by Stripe customer_id. Used by the /[handle] profile to render an analyst's claim-level track record — a separate signal from thesis-outcome accuracy. Only visibility='public' claims surface; private state never leaks. Accura
• list_public_theses_by_user ~247 tokens
  Return the PUBLIC theses + reputation aggregate for a user identified by Stripe customer_id. Used by the /[handle] profile page to render an analyst's track record. Only entries with visibility='public' are surfaced — private theses never leak. Reputation is correct/(correct+wrong) over graded these
• list_report_versions ~297 tokens
  Author-only newest-first listing of a report's archived version history. Each entry summarises what changed (sections edited, etc.) so the workspace UI can render a clickable history without loading every artifact. Pair with `get_report_version` to fetch a specific version's content for diffing agai
• list_restatements ~1428 tokens
  List financial-statement restatements — facts a later SEC filing materially changed (>0.5% swing) from what was originally reported. Each event carries the as-reported value, the restated value, the signed delta, a severity bucket, the RAW XBRL tag both filings used (the diff is same-tag, so it is a
• list_rules ~122 tokens
  Paginated newest-first listing of the caller's own rules. Tier: sp500+ (sample rejected).
• list_scheduled_tasks ~224 tokens
  Paginated newest-first listing of the caller's own scheduled (deferred) tasks — transparency into what an agent has queued for the future. Filter by `status` (pending/completed/cancelled/cancelled_owner_inactive/all). Tier: sp500+ (sample rejected).
• list_signal_inbox ~338 tokens
  Newest-first listing of the caller's in-app inbox. Items are signal FIRES with a `dashboard` channel — written by the cron evaluator (or `test_signal`) — plus platform notifications written by the edge-gateway (agent run completions, morning briefs, skipped runs); use list_signals instead for the si
• list_signals ~262 tokens
  Paginated newest-first listing of the caller's signals (id, condition, channel, status, trigger_count, evaluator health). Filter by `status` (active/paused/deleted/all). Use the returned signal id with delete_signal or test_signal. Tier: sp500+ (sample rejected).
• list_sops ~315 tokens
  List Valuein's expert research playbooks — the step-by-step procedures a senior equity analyst follows, each encoding the exact tool sequence, parallel-wave grouping, and output structure for one task (research brief, screen and shortlist, forensic quality audit, capital-allocation review, survivors
• list_theses ~299 tokens
  Return the caller's saved theses, newest-first. Filters: ticker (exact), view, status. Cursor-based pagination — pass `next_cursor` from the previous response to fetch the next page. Sample tier rejected (no per-user state).
• list_uploaded_documents ~144 tokens
  List the caller's currently-active uploaded documents (filename, size, char count — no full text; call get_uploaded_document for that). Uploads expire 24h after upload.
• list_watchlists ~264 tokens
  Paginated newest-first listing of the caller's watchlists (id, name, tickers, status, counts). Filter by `status` (active/archived/all). Returns metadata only — use get_watchlist for one list's full ticker set, or watchlist_diff for new filings across a list. Tier: sp500+ (sample rejected).
• mark_inbox_read ~202 tokens
  Set `read_at` on a single inbox item by its id (from list_signal_inbox or the signals feed resource) — not a signal id. Idempotent — re-marking does NOT reset the first-read timestamp; there is no unmark. Returns the new unread_count so the agent/UI can update its badge without a follow-up call. Tie
• match_derived ~654 tokens
  Check whether figures a report STATES can be reproduced by the engine from the SEC facts the report cites. For each `{ token, ticker, fact_ids }` it tries every registered margin, growth, share-of, difference and ratio formula over those facts and compares the rendered result to your token EXACTLY.
• project_three_statement ~942 tokens
  Linked forward Income Statement / Balance Sheet / Cash Flow projection, seeded from the company's latest historical annual period. The balance sheet ties out (assets == liabilities + equity) EVERY projected year by algebraic construction — each year's `tie_out_ok` field is a live correctness check,
• publish_claim Sends messages · ~270 tokens
  Make a saved claim discoverable by flipping its visibility: `public` (default) surfaces it on the author's /[handle] profile and counts toward their claim-accuracy reputation; `unlisted` makes it reachable at a known direct link but keeps it off the profile. Use AFTER save_claim to promote an existi
• publish_report Sends messages · ~482 tokens
  Publish a report for FREE at `listed` or `unlisted` visibility to build your public author profile. `listed` makes it discoverable via `search_reports` (keyword catalog search); `unlisted` keeps it out of the catalog but accessible by direct id (shareable link). Author can set a `tier_required` no h
• publish_thesis Sends messages · ~285 tokens
  Make a saved thesis discoverable by flipping its visibility: `public` (default) surfaces it on the author's /[handle] profile and counts toward their reputation aggregate; `unlisted` makes it reachable at a known direct link but keeps it off the profile. Use AFTER save_thesis to promote an existing
• read_filing_section ~794 tokens
  Read one section of a 10-K / 10-Q (or amendment) as plain text: MD&A (10-K `7`, 10-Q `I-2`), Risk Factors (`1A`, `II-1A`), Legal Proceedings, Controls, a financial-statement note (`note-3`), or the whole filing (`document`) when an Item is only a page pointer. To jump to a phrase, call find_in_filin
• reject_staged_action ~252 tokens
  Reject a staged action by id. Terminal — the underlying tool is NEVER called, and a rejected (or otherwise already-decided) action can never be flipped back by a later approve/reject call; `transitioned` tells you whether THIS call is what moved it to 'rejected' or whether it was already decided. An
• render_report ~619 tokens
  Return a 15-minute presigned download URL for a report in the requested binary format. `format=md` presigns the cached markdown — instant, no compute. `format=docx` and `format=pdf` return the SAME branded research-note design in the two media: a masthead-first page 1 (Valuein letterhead — brand ru
• restore_deleted ~831 tokens
  Undo a delete: restores a thesis, watchlist, signal, claim or report that `delete_*` archived, a rule, citation override or uploaded document that `delete_*` removed, a memory entry removed by `delete_agent_memory` (id = its key), an inbox item hidden by `dismiss_inbox_item` (id = inbox_id), a task
• run_agent ~289 tokens
  Fire one of the caller's own standing agents now, out of band from its schedule. For agent_type="autonomous" this costs money — it settles against the owner's own BYO LLM key first, falling back to the managed wallet only if funded; agent_type="workflow" runs are free/deterministic. This call can be
• run_backtest ~869 tokens
  A SMALL, BOUNDED, in-Worker sanity-check backtest — NOT a full-universe backtesting engine. Answers a quick question like 'does this factor actually work on these 5 names over the last year' inline, mid-conversation, without leaving MCP. Composes two existing tools (`get_pit_universe` + `get_pit_val
• run_workflow ~468 tokens
  Resolve a saved workflow by id and return a structured execution plan for a single ticker. Each plan entry names a real MCP tool or SOP plus its ticker-substituted arguments; the calling agent invokes them in order, applying any `skip_if` predicate against the previous step's output. **This tool do
• save_agent ~1346 tokens
  Create or update a standing agent — a saved {goal + tickers + schedule} that fires either a fixed step recipe (agent_type="workflow", free/deterministic) or an AI-directed team (agent_type="autonomous", charged — settles against the owner's BYO key first, falling back to the managed wallet only if f
• save_citation_override ~644 tokens
  Persist a correction of a citation value. The correction is keyed on the canonical `fact_id` (a stable hash of CIK + accession + concept + period) so it applies to every report that references that same fact — including agent-regenerated reports. Re-saving the same fact_id replaces the prior correct
• save_claim ~1596 tokens
  Persist a single falsifiable, evidence-backed CLAIM — the atomic unit of the research graph. Use this for each discrete assertion an analysis produces (e.g. 'NVDA gross margin stays above 70% through FY2026'), then compose claims into a thesis with `link_claim_to_thesis`. Claims are scored independe
• save_figure_review ~768 tokens
  Record (or update) the review state of ONE figure inside a report — the durable answer to 'has a human traced this number back to its filing?' Upsert keyed on (report_id, figure_key): re-reviewing a figure REPLACES its prior mark, it never appends, so this is always the figure's current state, never
• save_freeform_report ~981 tokens
  Save free-form markdown (e.g. a chat synthesis) as a DRAFT report you can refine in the editor and export to Word/PDF. Unlike `create_report` (which computes a structured reverse_dcf or thesis report), this accepts raw markdown and splits it into sections. PASS `citations` with the fact_ids behind t
• save_thesis ~764 tokens
  Persist a directional investment thesis (bull / bear / neutral) on a ticker. The thesis becomes part of the caller's private research diary; pair with `list_theses` + `score_thesis_outcome` to track conviction-vs-outcome over time. Pass `idempotency_key` for at-most-once semantics from a retrying ag
• save_watchlist ~421 tokens
  Upsert a named watchlist with a list of tickers. Replace semantics — the full ticker list is the source of truth for that name. Use this for both creation AND modification (delete + recreate is not required for edits). 500-ticker cap per list. Names are case-insensitive uniqueness. Optional `weights
• schedule_task ~476 tokens
  Defer a follow-up task ("re-check AAPL margin compression in 30 days") for up to 90 days. This is an AGENT-facing primitive — call it mid-conversation/mid-run when you decide something is worth re-checking later; it is NOT a human-authorable "new task" form (use the Workspace's standing-agent schedu
• score_claim ~388 tokens
  Resolve a claim's outcome. By default auto-grades an `auto` claim by evaluating its verifiable_condition against SEC fundamentals (confirmed/refuted), or marks it `needs_review` when it can't be resolved deterministically (judgment, antecedent, or missing data). To record a human/agent judgment inst
• score_due_claims ~344 tokens
  Find every auto-gradable claim that is due (assertions in open/needs_review/stale; predictions whose horizon has passed) and resolve each against fundamentals. Operates on the caller's OWN claims — omit `customer_id`. Targeting another user's `customer_id` is reserved for Valuein's internal scoring
• score_due_theses ~362 tokens
  Find every thesis past its horizon with no outcome yet, and grade each via `score_thesis_outcome`. Operates on the caller's OWN theses — omit `customer_id`. Targeting another user's `customer_id` is reserved for Valuein's internal scoring service and is rejected for every plan, including Institution
• score_thesis_outcome ~303 tokens
  Grade a saved thesis against fundamental momentum since its creation. Pulls revenue / operating-margin / EPS / OCF deltas and aggregates into a score in [-1, +1]. Bull theses are graded by directional alignment, bear by inverse, neutral by closeness-to-flat. The grade is persisted back to the thesis
• screen_universe ~949 tokens
  Rank companies by cross-sectional factor scores from factor_scores.parquet. Returns the underlying factors (roe, gross_margin, operating_margin, net_profit_margin, revenue_growth_yoy, fcf_to_assets, debt_to_equity, asset_turnover, current_ratio, piotroski_f_score) plus their percentile ranks (1.0 =
• search_companies ~1012 tokens
  Search for US public companies by name, ticker symbol, CIK (SEC identifier), or SIC industry code. Returns ticker, company name, sector, industry, exchange, and current S&P 500 membership status. Use this tool to resolve a company name to ticker/CIK before calling `get_company_fundamentals`, `get_va
• search_reports ~307 tokens
  Search the catalog of published research reports. All listings are free to read. Filters: free-text (matches title + abstract), ticker, report_type. Sort: `newest` (default) or `oldest`. Tier-gated: callers only see reports their plan tier can read.
• set_agent_memory ~276 tokens
  Store or update ONE durable memory entry (key → value) for this user so context survives across sessions — preferences, prior conclusions, working context. Replace semantics per key (reusing a key overwrites it). Do NOT store a number you would later cite as a fact: financial figures come from data
• sign_off_report ~496 tokens
  Request a Valuein compliance certificate for one of the caller's OWN reports — a signed, publicly verifiable attestation at valuein.biz/verify/{id} that every fact the report cited was knowable at the time it was used (absence of lookahead bias). It attests provenance ONLY: it says nothing about whe
• stage_action ~522 tokens
  Propose an MCP tool call for human approval BEFORE running it. Call this — instead of calling the tool directly — whenever an autonomous or unattended caller (a scheduled standing agent, an unattended agent-runner run, or any MCP client operating without a human watching) is about to perform a write
• submit_artifact_feedback ~1027 tokens
  File EXPLICIT, structured feedback about a specific artifact you (or the model) produced — a chat message, a report, a thesis, a claim, a tool call, or the schema. Use this (not `submit_feedback`) when you can name WHAT was judged and HOW: pass `target_type` + `target_id` + a `sentiment` (positive/n
• submit_feedback ~1115 tokens
  File product feedback to the Valuein team — a bug, feature request, experience note, or data-quality issue — directly from the agent surface. Available on EVERY tier including guest/sample (no token required), so an agent can report a rough edge in-band without the human leaving the conversation. Pr
• test_rule ~271 tokens
  Dry-run a rule's condition_expr against a SYNTHETIC trigger payload — reports whether it WOULD have fired, but NEVER dispatches the action (no report generated, no team run, no message sent, no inbox write). Use this immediately after create_rule to sanity-check the condition before it starts evalua
• test_signal ~257 tokens
  Fire a synthetic notification through EVERY channel the signal is configured with. Use this immediately after `create_signal` to verify the channels (email address valid / webhook URL reachable + HMAC verification on the receiver). The synthetic fire is logged with a `[TEST]` summary so it affects n
• unlink_claim_from_thesis ~266 tokens
  Remove the link between a claim and a thesis. Idempotent — succeeds whether or not the link existed. The claim and thesis themselves are untouched. Undoable: the response carries `prior_role` (supports/refutes/context, null when there was no link), so calling `link_claim_to_thesis` with the same the
• unpublish_claim ~164 tokens
  Revert a published claim (public or unlisted) back to `private` — removes it from the author's /[handle] profile and excludes it from the public claim-accuracy aggregate. The inverse of publish_claim. Owner-only, idempotent. Tier: sp500+ (sample rejected).
• unpublish_report ~114 tokens
  Revert a published report (listed or unlisted) back to `private` visibility, removing it from the public catalog. Author-only. Idempotent.
• unpublish_thesis ~164 tokens
  Revert a published thesis (public or unlisted) back to `private` — removes it from the author's /[handle] profile and excludes it from the public reputation aggregate. The inverse of publish_thesis. Owner-only, idempotent. Tier: sp500+ (sample rejected).
• update_report ~1265 tokens
  Replace one or more sections of an existing report owned by the caller. Useful for authoring workflows where the agent's first draft (`create_report`) is refined by additional analysis before publishing. Pass `citations` for figures in the edited prose — they are MERGED into the report's existing se
• update_signal ~1833 tokens
  Edit an existing signal IN PLACE — rename it, change what it watches, or change where it delivers — keeping its id, its fire history (`trigger_count`, `last_triggered_at`) and every inbox item and delivery already tied to it. Pass only the fields to change; omitted fields keep their stored value. `c
• verify_fact_lineage ~1210 tokens
  Use this tool when the user asks BOTH what a financial figure is AND which filing reported it — e.g. "What was Apple's most recently reported revenue, and which 10-Q filed it?" or "Show me the accession ID for Tesla's latest net income." Returns a single fact plus its complete filing provenance: ent
• verify_facts ~1062 tokens
  Resolve MANY cited facts to their SEC filings in ONE call — the batch form of `verify_fact_lineage`. Use this whenever you are checking a LIST of figures rather than a single number: reviewing a report's citations, auditing a thesis's evidence, or confirming every figure in a draft before you sign i
• verify_report_figures ~673 tokens
  Check EVERY number in one of your own reports against the filing it cites, in one call. Returns a verdict per figure: `matches` (the prose quotes the filing's own rendered string), `differs` (positive evidence the filing says something else — the report is wrong), or `not_checkable` (no comparison w
• watchlist_diff ~539 tokens
  Return new SEC filings across a set of companies since a given date. Name the companies EITHER with `name` (a watchlist you have already saved) OR with `tickers` (a list you are holding right now) — pass exactly one. Use `tickers` for an ad-hoc question: there is no need to create a watchlist just t

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