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  3. MCP Polygon)
MCP Polygon) logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 5:00:54 PM

MCP Polygon)

User RatingsBe the first to rate and review this MCP server!
View Repository390 GitHub StarsTotal stargazers on GitHub for the source repository (390 stars).Visit Website
financemarket-datastockssqlmcp

Access Massive.com market data through MCP tools for endpoint discovery, API calls, SQL analysis, and financial calculations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "polygon-io-mcp-polygon": {
      "command": "uvx",
      "args": [
        "--from"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (3) Directory Badge Claim listing AlternativesπŸ’° More in Finance & Fintech

Overview

The polygon-io/mcp_polygon) MCP server exposes Massive.com financial market data through three composable MCP tools. It searches endpoint documentation, calls REST APIs, stores selected results in an in-memory SQLite database, and runs SQL over stored data. Built-in functions cover option Greeks, returns, and moving averages. Reach for it when an agent needs stock, options, forex, crypto, futures, reference, or related market data and analytical post-processing.

Use cases

β€’Query historical stock prices and trading volume
β€’Compare market gainers and losers
β€’Analyze stored market data with SQL
β€’Calculate option Greeks
β€’Compute moving averages and risk-adjusted returns

Key features

β€’Natural-language endpoint discovery
β€’Massive.com REST API access
β€’In-memory SQLite data storage
β€’SQL queries with CTEs and window functions
β€’Financial functions for Greeks and returns
β€’SMA and EMA calculations

Capabilities & Tool Schemas (3) ~167 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Polygon).

search_endpoints

Search for API endpoints and built-in functions by natural language query. Returns titles, path patterns, and descriptions. Set `detail` to `"more"` for query parameter docs, or `"verbose"` for full documentation. Use `max_results` to limit results.

call_api

Call any Massive.com REST API endpoint. Supports storing results as an in-memory database table (`store_as`) and applying post-processing functions (`apply`). Paginated responses include a next-page hint.

query_data

Run SQL against stored SQLite DB. Supports `SHOW TABLES`, `DESCRIBE <table>`, `DROP TABLE <table>`, CTEs, window functions, and more. Results can also be post-processed with `apply`.

How MCP Polygon) works

What polygon-io/mcp_polygon) MCP server does

The polygon-io/mcp_polygon) MCP server provides an MCP interface to the full Massive.com financial data API. Its data coverage includes stock, options, forex, crypto, and futures aggregates; historical and real-time trades and quotes; snapshots; ticker reference data; dividends; splits; IPOs; fundamentals; analyst ratings; news; treasury yields; inflation data; and market status information.

Rather than defining a separate MCP tool for every financial endpoint, it exposes a smaller set of composable operations. An agent can discover an endpoint, call it with the required parameters, save the response for later analysis, and query the saved data with SQL.

How it works

search_endpoints searches the dynamically indexed API documentation and built-in functions using natural language. Results can include endpoint titles, path patterns, descriptions, query parameter details, or full documentation depending on the requested detail level. The index is loaded from Massive.com's llms.txt document at startup.

call_api sends requests to Massive.com REST endpoints. Responses may be stored as in-memory SQLite tables with store_as, and post-processing can be applied through the apply parameter. Paginated responses provide a hint for retrieving the next page.

query_data executes SQL against stored tables. Supported operations include table inspection and deletion, common table expressions, window functions, and other SQLite queries. Results can also be passed through built-in post-processing functions.

Setup and configuration

The polygon-io/mcp_polygon) MCP server requires Python 3.12 or newer, Astral UV 0.4.0 or newer, and a Massive.com API key. The documented installation uses UV to install the mcp_massive package from the project's Git repository. Claude Desktop can then launch the installed mcp_massive binary over the default STDIO transport.

Set MASSIVE_API_KEY to authenticate requests. POLYGON_API_KEY remains available as a deprecated alias. Optional settings can change the transport, API base URL, endpoint-index URL, maximum number of in-memory tables, and maximum rows per stored table. Supported transports are STDIO, SSE, and streamable HTTP; STDIO is the default.

Tools and capabilities

  • Search API endpoints and built-in functions with natural-language queries.
  • Call any supported Massive.com REST endpoint.
  • Store API responses in temporary SQLite tables.
  • Inspect, query, and remove stored tables with SQL.
  • Apply Black-Scholes price and Greek calculations, including delta, gamma, theta, vega, and rho.
  • Calculate simple, logarithmic, and cumulative returns, Sharpe ratio, Sortino ratio, SMA, and EMA.

Limitations and notes

The polygon-io/mcp_polygon) MCP server is marked experimental, so breaking changes may occur. It depends on access to the Massive.com API and its applicable terms and privacy policy. Stored data is held in an in-memory SQLite database, with configurable limits of 50 tables and 50,000 rows per table by default. The README states that the server does not store or cache user data and proxies requests to Massive.com.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
390
Stargazers on the source repository.
Last commit
3mo ago
Most recent push to the default branch.
Tools exposed
3
Callable tools this server registers over MCP.
Directory activity
3 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about MCP Polygon)

Install Python 3.12+, UV 0.4.0+, and a Massive.com API key, then install the documented mcp_massive package from the project's Git repository with UV.

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Technical Specs & Signals

CategoryπŸ’°Finance & Fintech
PricingBring your own API key (usage-based cost)
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
AuthAPI key
ClientsClaude Desktop
Last updatedSep 7, 2026
9/10 checks healthy over the last 33d
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars390
GitHub Star CountTotal stargazers on GitHub representing community popularity (390 stars).
Last commit3mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jun 11, 2026
57Quality signal: Good Β· 57/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools27/30
Adoption & activity6/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 20d ago via OSV.dev Β· --from (PyPI)

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