sugra-api-mcp

_{Published in the official OpenAI Plugins Directory. Available for ChatGPT and Codex.}

Give any AI agent access to 1,500+ data endpoints across markets, economics, companies, government, news, climate, maritime and entity screening - through one MCP server.

Works with ChatGPT, Claude, Gemini, xAI, Cursor, VS Code and any MCP client.

Official Model Context Protocol server for the Sugra API: one connector, a bundled endpoint catalog, and structured tool results with source attribution on every answer.

See it in action

An agent answering a real question end to end - resolving entities, pulling live snapshots and history, and citing the source and freshness on every number:

More examples:

Macro research - one prompt builds a full G7 inflation and policy-rate table, each cell dated and sourced, with the unavailable ones flagged rather than faked:

Cross-domain snapshot - Brent crude, marine weather and regional risk pulled together for a shipping desk, each with its source and timestamp:

What a session looks like

Hosted MCP transcript (the three composed tools shown here run on the hosted endpoint). Captured example - wording and figures vary by run and as new BLS data is published:

User: Where does US inflation stand, and how has it trended over the past year?

resolve_entity("US inflation")
  -> macro indicator cpi_us (U.S. Bureau of Labor Statistics)
get_snapshot("cpi_us")
  -> latest reading with freshness, provenance and quota cost
get_timeseries("cpi_us", metric="macro_series", range="1y")
  -> 12 monthly points with an explicit downsampling flag

Agent: US CPI printed 2.9% year over year in the latest release, down from
3.5% twelve months earlier - a steady decline since spring.
Source: U.S. Bureau of Labor Statistics via the Sugra API.

Every tool result carries structured metadata - source attribution, freshness, and rate-limit cost - so agents can cite sources and budget requests instead of guessing.

How it works

flowchart LR
    A["AI agent<br/>(ChatGPT, Claude, Gemini, xAI, IDEs)"] --> B["Sugra MCP<br/>hosted: 11 tools / local: 8 tools"]
    B --> C["Sugra API<br/>1,500+ endpoints, 36 data domains"]
    C --> D["160+ primary sources<br/>markets, economics, government,<br/>news, climate, maritime"]

Behind the gateway sits the Sugra API: 160+ primary sources - sovereign statistics agencies, central banks, intergovernmental bodies and more - feeding 1,500+ endpoints across 36 data domains. The server ships a bundled catalog of the full endpoint surface, so discovery (search, describe, toolsets) runs locally without network calls; only actual data requests hit the API.

What agents build with it

Five official skills ship as MCP resources (sugra://skills/...) and as SKILL.md drop-ins for Claude, Codex, and Cursor: explore the catalog, envelope and attribution, auth and rate limits, hosted vs gateway, and a cross-domain briefing pattern. Copy a skill directory from sugra_api_mcp/skills/ into the client's skills folder, or resources/read the matching URI after connect.

Six workflow prompts ship with the server and turn these into one-click flows in clients that surface MCP prompts:

• Market and macro research - "Compare inflation and central bank policy rates across the G7." (macro_briefing)
• Equity snapshots with sources - "Where does NVIDIA stand today - price, profile, and market backdrop?" (market_snapshot)
• Sanctions and compliance screening - "Screen this supplier and resolve its LEI identity." (sanctions_screening)
• Sector comparison - "Energy versus technology: valuations and flows side by side." (sector_compare)
• Climate, maritime and trade intelligence - "Red Sea shipping this week: chokepoint transits, crude price, and weather on the route." (earth_conditions plus the transport and commodities catalog)
• Source discovery - "What does the catalog offer for fixed income, and from which institutions?" (source_overview)

Every answer carries source attribution and freshness metadata, so agents cite instead of guessing.

Hosted MCP (recommended)

No install. Point your client at the hosted Streamable HTTP endpoint:

https://app.sugra.ai/mcp

• 11 tools: the eight gateway tools plus three composed agent tools (resolve_entity, get_snapshot, get_timeseries)
• OAuth sign-in through the claude.ai and ChatGPT connector UIs, or Authorization: Bearer sugra_xxx_... with an API key
• In claude.ai: Settings -> Connectors -> Add custom connector
• In ChatGPT: Settings -> Connectors -> Add MCP server

Local package

Runs on your machine over stdio (or self-hosted HTTP) with an API key:

pip install sugra-api-mcp

• Eight gateway tools
• stdio for desktop clients and IDEs, Streamable HTTP for self-hosting
• Authenticates with SUGRA_API_KEY

Get a free API key at app.sugra.ai/settings/billing (Free tier: 50 req/day).

Quick start

pip install sugra-api-mcp
export SUGRA_API_KEY=sugra_xxx_...   # free key: app.sugra.ai/settings/billing
sugra-api-mcp call quotes_symbol_price --params '{"symbol":"AAPL"}'

The same call through an agent: connect the server to your client (next section) and ask "What is AAPL trading at? Use Sugra." The agent finds quotes_symbol_price in the catalog and calls it with the symbol.

Connect your client

Supported clients:

• Anthropic Claude: Claude Desktop, Claude Code (CLI), claude.ai (web)
• OpenAI GPT: ChatGPT (via MCP connector)
• Google Gemini: Gemini CLI, Gemini Code Assist (VS Code + JetBrains)
• xAI: Remote MCP Tools in xAI SDK and Responses API
• IDEs: VS Code (native), Cursor, Zed, Cline, Continue.dev, Windsurf
• Custom agents: anything built on the Python or TypeScript MCP SDK

Claude Desktop (stdio)

Add to claude_desktop_config.json:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: Claude Desktop has no Linux build. On Linux, pip install sugra-api-mcp and use Claude Code (CLI), an IDE client, or the hosted HTTP endpoint below.

{
  "mcpServers": {
    "sugra": {
      "command": "sugra-api-mcp",
      "env": {
        "SUGRA_API_KEY": "sugra_xxx_yourkey..."
      }
    }
  }
}

Restart Claude Desktop. Sugra tools appear in the tools menu.

Claude Code (Anthropic CLI)

claude mcp add sugra -- sugra-api-mcp
# then set the env var that sugra-api-mcp reads
export SUGRA_API_KEY=sugra_xxx_...

Or edit ~/.claude/config.json manually with the same shape as Claude Desktop above.

Usage with Gemini CLI

Gemini CLI reads MCP servers from ~/.gemini/settings.json (user scope) or .gemini/settings.json in the project. For a local stdio install, add:

{
  "mcpServers": {
    "sugra": {
      "command": "sugra-api-mcp",
      "env": {
        "SUGRA_API_KEY": "sugra_xxx_yourkey..."
      }
    }
  }
}

If the console script is not on PATH, use "command": "python" with "args": ["-m", "sugra_api_mcp"] instead. The equivalent Gemini CLI command is:

gemini mcp add --scope user -e SUGRA_API_KEY=sugra_xxx_yourkey... sugra sugra-api-mcp

Or connect to the hosted endpoint without installing the package:

gemini mcp add --scope user --transport http \
  --header "Authorization: Bearer sugra_xxx_yourkey..." \
  sugra https://app.sugra.ai/mcp

Run gemini mcp list to check the connection, then enter /mcp in an interactive session to inspect the available tools. A local stdio connection shows the eight gateway tools in Tool reference; the hosted endpoint also shows the three hosted-only agent tools. If a local server does not connect from a new directory, review and trust that workspace with gemini trust before retrying.

These examples were checked against the Gemini CLI MCP documentation and Gemini CLI v0.51.0.

Cursor, Zed, Cline, Continue.dev, Windsurf

Each of these has an MCP settings file (typically mcp.json or equivalent) with the same stdio config shape as Claude Desktop.

ChatGPT