MCP server

Onvexia: Crypto Fundamentals, Sentiment & Onchain Tracking Official

com.onvexia/onvexia

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Crypto fundamentals, sentiment, whale tracking and influencer call accuracy for traders and agents.

Website Source

At a glance

Type

MCP server

Publisher

onvexia.com (verified by the MCP Registry)

Status

Working at last check

Tools

66

Token cost

About 10,331 tokens per request

Sets up in

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

Last checked

26 Oct 2026, 08:29 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 onvexia https://onvexia.com/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.onvexia]
url = "https://onvexia.com/mcp"

Gemini CLI

{"mcpServers":{"onvexia":{"httpUrl":"https://onvexia.com/mcp"}}}

Cursor

{"mcpServers":{"onvexia":{"url":"https://onvexia.com/mcp"}}}

VS Code

{"servers":{"onvexia":{"type":"http","url":"https://onvexia.com/mcp"}}}

Antigravity

agy mcp add onvexia https://onvexia.com/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":"onvexia","server_url":"https://onvexia.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"onvexia","server_url":"https://onvexia.com/mcp"}

Tools

• analyze_sentiment ~164 tokens
  Score any text for crypto sentiment, tuned for crypto slang and tickers. Takes arbitrary text you supply — it does not look anything up. General sentiment models read "this is going to zero" and "wagmi" badly; this one is fitted to the register. Returns polarity plus the ter
• get_address_coverage ~72 tokens
  What we index per chain for watched addresses: what we see, what we miss, and what an empty feed actually means.
• get_address_events ~99 tokens
  Events on watched addresses. Check get_address_coverage before reading an empty result as silence — below the observed USD floor, movement is invisible to us.
• get_agent_findings ~131 tokens
  What this platform's own monitoring agents are currently complaining about — dead collectors, stale data streams, coverage drops. Worth checking before relying on a number: a stream flagged stale here is still being served, it is just old.
• get_ai_substance ~307 tokens
  Does an AI-sector project actually ship code, against how much attention it gets. Four states, and the fourth is not a verdict: ships public repo with development activity in 30 days silent public repo, no activity in 30 days no_publi
• get_aspect_sentiment ~153 tokens
  Split an asset's sentiment by what people are actually talking about: technology, price, team and community. The aggregate can be flat while the parts disagree sharply — bullish on technology, bearish on team is a different situation from uniformly neutral, and only
• get_asset ~155 tokens
  An asset's core profile by symbol: name, category and cross-system identifiers (CoinGecko id, contract addresses, chains). Start here when you have a ticker and need to be sure which asset it refers to. Tickers collide across chains — if the symbol is ambiguous, reso
• get_asset_fundamentals ~307 tokens
  Get the full fundamental brief for an asset: market snapshot, supply and valuation, project, TVL, revenue, treasury, security, governance, unlock schedule, derivatives positioning, competitive rank, valuation ratios and a graded scorecard — in one call. READ THE SECT
• get_asset_platforms ~84 tokens
  Every chain an asset is deployed on, with its contract address and token decimals.
• get_asset_revisions ~114 tokens
  Metrics for this asset that CHANGED after they were first published, with the old value, the new one and why. An agent that quoted an earlier number can find out here that it moved.
• get_asset_scores ~179 tokens
  An asset's Galaxy Score and AltRank, with the components behind each. Galaxy Score is a composite of social and market health on a 0-100 scale; AltRank is relative standing against the rest of the universe, where 1 is best. READ THE COMPONENT BREAKDOWN — a score moved by
• get_asset_social_signal ~101 tokens
  Per-asset social signal over time. The `available` field states plainly whether we hold it.
• get_asset_technicals ~292 tokens
  Get support and resistance merged across 1w/1d/4h/1h, per-timeframe indicators, and derived spot/long/short setups for an asset. Each level carries the timeframes that confirmed it and the method on each — a level agreed by four charts is a different claim from one seen
• get_bot_detections ~240 tokens
  Accounts flagged as automated or coordinated, with the behavioural evidence. Volume from these should not be read as organic attention. READ `coverage` AND `note` BEFORE YOU READ THE LIST. No scorer is currently running, so `bot_probability` is NULL for every account and
• get_chain_coverage ~108 tokens
  Per-chain coverage — tokens mapped, labelled addresses, whale transactions seen, and how many were attributed to a named entity. Attribution is Etherscan-derived, so it is strong on Ethereum and sparse on other chains.
• get_constellation ~79 tokens
  Asset co-mention graph — which assets are discussed together, with what was filtered out.
• get_coordinated_campaigns ~98 tokens
  Detected coordinated posting campaigns — the same message pushed by multiple accounts. Matching is exact-text, so this catches copypasta and misses the same campaign reworded.
• get_correlation ~152 tokens
  How closely an asset's social activity tracks its price, with the lead/lag. Correlation is not causation and this endpoint does not claim it is. A high coefficient says the two series moved together over the window — it does not say which one moved first. Use get_leading_ind
• get_creator_rankings ~158 tokens
  Rank social creators across the whole corpus by measured influence. Corpus-wide, unlike get_influencers which is scoped to one asset. Influence is computed from engagement our collectors actually observed, so a creator we do not ingest is absent rather than ranked low — an
• get_data_coverage ~114 tokens
  What data this platform actually holds right now: asset count, how many are priced, chains covered, labelled addresses, social corpus size, and freshness timestamps. Call this to check whether an answer is supportable before asserting it.
• get_disclosures ~361 tokens
  Public-record documents about issuers we track: SEC filings and federal court dockets. Exists because both RWA failures of 2026 were disclosed in public text before the price moved -- RealT's tax delinquency sat in court filings for a year, Goldfinch's borrower defau
• get_emerging_dex_pairs ~162 tokens
  Newly created DEX pairs above a USD liquidity floor. THE FLOOR IS RETURNED IN THE RESPONSE, and it is load-bearing: this is the long tail where most pairs are rugs or noise, and the floor is the only thing separating a signal from a list of scams. Raising it shrinks
• get_entities ~112 tokens
  Named entities extracted from social documents about an asset — people, organisations, products and other tickers mentioned alongside it. Use it to find what a narrative is actually about.
• get_entity_flows ~106 tokens
  Whale flow per labelled entity over the window. Inflow to an exchange is distribution pressure; outflow is accumulation.
• get_exchange_flows ~174 tokens
  Net movement of an asset into and out of exchange wallets. Inflows are supply arriving somewhere it can be sold; outflows are supply leaving to self-custody. The conventional reading is distribution vs accumulation, but a single large transfer can be an exchange reba
• get_exchange_listings ~136 tokens
  Recent exchange listing announcements — an asset being added to a venue. A listing is an ATTENTION event, not a fundamental one: it changes who can buy, not what the project is worth. Use it to explain a volume or social spike, not as a valuation input.
• get_exchange_netflow ~94 tokens
  Per-token flow onto and off exchanges. Inflow is distribution pressure, outflow is accumulation. net_usd where the token can be priced.
• get_hodl_waves ~78 tokens
  Bitcoin supply split by coin age over time — which cohorts are holding and which are moving.
• get_influencer_leaderboard ~273 tokens
  The influencer leaderboard, ranked by what people actually got RIGHT rather than by how loud they are. rank_by="accountability" (default): scored Predictor vs Reactor — did the call come before the move, or after it. rank_by="accuracy": ranked by how often their pric
• get_influencer_ledger ~299 tokens
  Get an influencer's track record. `view` picks one of three records: accountability (default) — did their calls precede the move (Predictor) or react to it (Reactor)? Hit rate and track record. accuracy — did their price calls come true? Hit rate over 30/90/180 days
• get_influencers ~156 tokens
  The accounts driving conversation about one asset, by reach and engagement. Ranked by measured activity in our corpus, NOT by follower count, and NOT by whether they were right — see get_influencer_ledger for track record. A large account posting noise ranks here; that is th
• get_leading_indicators ~161 tokens
  Which social and on-chain signals have historically MOVED FIRST for an asset. This is the lead/lag question that get_correlation deliberately does not answer. A lead measured over a past window is not a forecast and the response does not present it as one — it is the observe
• get_metric_metadata ~168 tokens
  Describe one metric before you use it: parity, category, minimum interval and any caveat attached to it. CALL THIS BEFORE get_metric_timeseries if the metric is unfamiliar. The minimum interval tells you the finest resolution that is real rather than interpolated, an
• get_metric_revisions ~87 tokens
  Restatements of published numbers — what changed, over which period, and why. A correction is not a market move.
• get_metric_timeseries ~255 tokens
  Timeseries for any available metric on any asset. Accepts Santiment-style relative dates ("utc_now-7d") as well as ISO timestamps. If the metric is not available this returns an error naming it rather than an empty series — an empty result here always means "no data in
• get_metric_timeseries_multi ~217 tokens
  Timeseries for ONE metric across MANY assets in a single call. `assets` is comma-separated (e.g. "BTC,ETH,SOL"). Prefer this over looping get_metric_timeseries — it is one round trip instead of N, and the values are guaranteed to come from the same read.
• get_metrics_batch ~112 tokens
  Latest value of MANY metrics for ONE asset in a single call. `metrics` is comma-separated. The mirror of get_metric_timeseries_multi.
• get_narrative_clusters ~120 tokens
  The raw clusters behind the stories, without the prose — for a model doing its own summarisation. Every cluster has >= 2 distinct authors; near-identical posts from one account are copypasta and excluded.
• get_narrative_rotation ~350 tokens
  Which crypto narrative is GAINING or LOSING attention share, with a liquidity confirmation leg. Compares the last `days` against the equally long window immediately before. Covers the 2026 narrative set — RWA, tokenized equities and treasuries, stablecoins, DePIN, pe
• get_ohlcv ~147 tokens
  Daily candles (open/high/low/close/volume) for an asset, with the venue they came from. Coverage is bounded by which assets have a USDT pair on Binance or Bybit — an asset absent here has no candle source we collect, which is not the same as having no price.
• get_research_report ~124 tokens
  One asset's generated report. The `unavailable` field lists metrics the report could NOT use — read it, because a report that silently omits funding rate reads as a report about an asset with unremarkable funding.
• get_sentiment_trends ~139 tokens
  Sentiment over time for an asset, with sample size and confidence interval. IMPORTANT: sentiment measured on few documents is unreliable — our own bootstrap put the direction wrong 35.6% of the time at n=1 and 9.5% at n=20. Read n before quoting a direction.
• get_signal_integrity ~114 tokens
  Get the Signal Integrity score (0-100) — is the move real or exit liquidity? Fuses social authenticity + on-chain reality + fundamental backing, with an Exit Liquidity Radar flag.
• get_similar_posts ~98 tokens
  Posts nearest a given post in embedding space. Read the returned BAND, never the raw cosine — 43% of this corpus sits at 0.80-0.90 by default.
• get_social_coverage ~150 tokens
  How many assets actually clear the document floor that makes each social metric computable. Call this BEFORE quoting sentiment for an asset. A large corpus total does not mean sentiment works everywhere: attention is a power law and the documents pile onto BTC, so mo
• get_social_dominance ~189 tokens
  Each asset's SHARE of total social attention over a window, with the posts, distinct authors, engagement and sentiment behind the share. Share is relative and sums across the universe, so an asset's dominance can fall while its absolute volume rises — that is the market gett
• get_social_posts ~102 tokens
  Collected social posts, optionally filtered by platform (bluesky, farcaster, reddit, 4chan, bitcointalk, rss).
• get_sql_schema ~66 tokens
  List every relation and column queryable via run_sql, plus the rules and what is deliberately not exposed.
• get_story_posts ~139 tokens
  The individual posts a story was assembled from — the receipts. Call this whenever a story matters enough to check. A generated story is a summary over these posts; this is how you verify it says what the sources say rather than taking the summary on trust.
• get_top_altranks ~139 tokens
  The assets ranked best by AltRank right now — relative standing, not absolute. AltRank is a RANK: 1 is the strongest in the universe. A rising AltRank in a falling market means outperforming the fall, not going up. Pair with get_asset_scores when the distinction matters.
• get_top_galaxy_scores ~157 tokens
  The assets with the strongest Galaxy Score right now. Galaxy Score is 0-100 and composite: social volume, engagement, sentiment and market health folded together. A high score is a statement about ATTENTION AND HEALTH, not about valuation — it does not mean an asset
• get_topic_rank ~172 tokens
  Rank what the market is TALKING ABOUT — themes and narratives, not assets. Ranked by mentions weighted by engagement over the window, so a topic posted about loudly by few accounts does not outrank one discussed widely. Use get_trending_assets for tickers; this is the layer
• get_trending_assets ~73 tokens
  Assets trending now by social activity, with the hype score that separates a real move from a burst of noise.
• get_trending_stories ~145 tokens
  Current narratives, each an LLM summary of a CLUSTER of posts rather than a single document. Read author_count before quoting one: a high post_count with a low author_count is one person repeating themselves, not a narrative. These are machine summaries, not edited a
• get_whale_transactions ~202 tokens
  Recent large on-chain transfers, optionally filtered to one asset. "Whale" is a SIZE threshold, not an identity. A large transfer is very often an exchange moving its own funds between wallets, which is not a market action at all — counterparty labels are included where we h
• get_wrapper_basis ~263 tokens
  Cross-wrapper spread for tokenized equities: one real company, every issuer that tokenizes it, and how far apart they trade. SpaceX trades under five wrappers and they do not agree. Spreads run roughly 0.1-0.9 percent between programs referencing the same share. Thi
• list_labelled_addresses ~150 tokens
  Browse labelled addresses, filtered by chain, entity (e.g. Binance) or category (exchange | bridge | dex | mev | staking | mining | sanctioned).
• list_metrics ~196 tokens
  List every metric Onvexia knows, with its parity and caveats. parity=exact means we compute it the way Santiment does; approximate means same concept but different coverage or method (read the caveat before relying on the number); unavailable means we do NOT serve it yet.
• list_nl_screens ~116 tokens
  Previously compiled natural-language screens: the English somebody wrote and the filter it compiled to, INCLUDING refusals. Useful as worked examples of the screener's filter grammar before you write one.
• list_research_reports ~132 tokens
  List the assets that currently have a generated research report available. Returns the index, not the reports — call get_research_report with a symbol for the body. An asset missing from this list has not been written up; that is a statement about our coverage, not about the
• lookup_address ~133 tokens
  Identify a blockchain address — exchange, bridge, DEX, MEV bot, mining pool, or OFAC-sanctioned — with the source and confidence of each label. IMPORTANT: `known: false` means no label is held. It does NOT mean the address is clean or unflagged.
• resolve_ticker ~154 tokens
  Does a bare ticker actually mean the crypto asset? verdict 'crypto' means mentions are about the asset; 'equity'/'other' means the bare word is dominated by something else (TIA is Spanish 'tia'; GRT collides with 'graph'). A 404 is NOT a clean bill of health — it mea
• run_sql ~102 tokens
  Run a read-only SELECT against the platform's data. One statement, 15s timeout, 10,000-row cap; truncation is always reported. Call get_sql_schema first for the queryable relations.
• screen_assets ~204 tokens
  Filter the whole asset universe server-side and return the matches. `filter` is comma-separated `field:op:value` terms, e.g. "market_cap:gt:1000000000,funding_rate:lt:0" — assets over $1B whose funding rate is negative. Ops: gt, gte, lt, lte, eq, ne. Call screener_fi
• screener_fields ~76 tokens
  Every field the screener accepts, with type and description. Call this before building a filter rather than guessing field names.
• search_assets ~121 tokens
  Search the whole asset universe (~1,900 assets) by symbol or name. Use this to resolve a user's loose reference into a real symbol before calling the other tools.

Browse

• Etherscan tools
• Email marketing
• Stocks and markets
• Crypto and blockchains

Related MCP servers

• Agent Einstein — Crypto & Market Intelligence
  AI price forecasts, whale flows, market sentiment and prediction signals. 18 tools free, no account.
• CryptoData API
  Crypto MCP with 21 tools for market data, DeFi, analytics, and sentiment. Post-paid USDC billing.
• Whale Insights
  Free read-only crypto whale-tracking & market-data MCP tools across 14 chains. No auth.
• AgentData — crypto market data with a checkable record
  Verifiable crypto signals, recorded history and always-on monitoring for AI agents via x402 on Base.
• f1ow
  Crypto market data & research MCP: price, derivatives, on-chain, sentiment, news, catalysts.
• Solenrich
  Solana onchain intelligence for AI agents: wallet risk, due-diligence, perps funding, smart money.
• Whale Data
  Real-time whale trades, Smart Money Radar, market snapshots, news sentiment, signal outcomes.
• ChainRay
  Multi-chain on-chain intelligence for AI agents through a public remote MCP server.

Badge for your README

[![AptLynx](https://aptlynx.net/badge/com.onvexia/onvexia.svg)](https://aptlynx.net/servers/com.onvexia/onvexia)

Listing text is written by the maker; AptLynx lists tools and does not vouch for them. Find another tool · Browse by topic · For agents