MCP server

Sugra API Official

ai.sugra/api-mcp

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

Gateway between LLM agents and world data through eight tools and a bundled endpoint catalog.

Source

At a glance

Type

MCP server

Publisher

sugra.ai (verified by the MCP Registry)

Status

Working at last check

Tools

11

Token cost

About 6,220 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 api-mcp https://app.sugra.ai/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.api-mcp]
url = "https://app.sugra.ai/mcp"

Gemini CLI

{"mcpServers":{"api-mcp":{"httpUrl":"https://app.sugra.ai/mcp"}}}

Cursor

{"mcpServers":{"api-mcp":{"url":"https://app.sugra.ai/mcp"}}}

VS Code

{"servers":{"api-mcp":{"type":"http","url":"https://app.sugra.ai/mcp"}}}

Antigravity

agy mcp add api-mcp https://app.sugra.ai/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":"api-mcp","server_url":"https://app.sugra.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"api-mcp","server_url":"https://app.sugra.ai/mcp"}

Tools

• call_endpoint ~1201 tokens
  Call a Sugra API endpoint by operation_id from the bundled catalog. Plan calls with describe_endpoint's agent_hints: duration_class "fast" usually responds in under ~2s, "slow" usually 1-5s and occasionally 15s+ on a cold upstream, "heavy" can exceed the gateway timeout - keep parallel calls within
• describe_endpoint ~238 tokens
  Describe one Sugra API endpoint by operation_id. Includes agent_hints (duration_class fast/slow/heavy, max_concurrency, bulk billing) so you can budget timeouts and parallelism before calling. POST endpoints with a JSON body also carry request_body_schema (the resolved JSON schema) - construct the
• fetch_data ~1416 tokens
  One-step fetch: find the best Sugra endpoint for the query and call it. Combines search_endpoints + call_endpoint into a single round trip. Use this when you want data without manually picking an operation_id. The full search_endpoints + describe_endpoint + call_endpoint dance is still available wh
• get_snapshot ~394 tokens
  Composed current view of an entity via a named recipe. Executes a fixed server-side recipe (company_snapshot, etf_snapshot, quote_snapshot, macro_indicator_snapshot, macro_calendar, earnings_snapshot, debt_snapshot) and returns one envelope with freshness, provenance, per-component coverage, and bi
• get_timeseries ~807 tokens
  Bounded timeseries for an entity: price, macro_series, etf_flows or etf_monthly_flows. Returns points oldest-first with an explicit downsampling flag when the raw series exceeded max_points. Times are UTC. Costs 1 unit per call. Read the step from ``served_granularity``, not ``granularity``. The l
• list_sources ~83 tokens
  List source families in the bundled catalog with endpoint counts. Use the family names as the source filter on search_endpoints. This does not call the Sugra API.
• list_toolsets ~92 tokens
  List catalog groups with endpoint counts and short descriptions. Use the group names as the toolset filter on search_endpoints. This does not call the Sugra API; it reads the bundled catalog.
• resolve_entity ~375 tokens
  Resolve free text to a canonical market or macro entity. Turns a ticker, company name, macro indicator, coin, or currency pair into the agent plane's ``{namespace, ids}`` entity for use with get_snapshot and get_timeseries. A cross-namespace collision (e.g. a ticker that is both an equity and a coi
• search_endpoints ~546 tokens
  Search the bundled Sugra endpoint catalog by natural-language query. Use this to pick an operation_id. It does not fetch data. Typical loop: 1. search_endpoints(query) -> ranked hits with required_parameters 2. describe_endpoint(operation_id) -> params, request_body_schema, agent_hints 3. call_endp
• sugra_entity_lookup ~575 tokens
  Resolve an entity by identifier and return its composed KYB envelope. `anchor` is `lei` (Legal Entity Identifier, resolved via the GLEIF registry) or `vat` (EU VAT number, validated via the EU VIES service). The result weaves identity, a sanctions screening signal, and - on request - ownership and
• sugra_entity_screen ~493 tokens
  Screen a person or organization name against the Sugra sanctions corpus. Returns a SCREENING SIGNAL, not a compliance determination. Sugra is a technology provider, not a sanctions authority or consumer reporting agency. PEP and adverse-media coverage is supplementary and non-comprehensive - a `cle

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