Standardizes SEC and ESEF XBRL fundamentals with source-linked facts, comparisons, screening, and restatement analysis over MCP.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Hub Equity MCP.
The Hub-Equity MCP MCP server gives MCP clients a consistent interface to financial facts from US SEC EDGAR and European ESEF filings. Instead of requiring an agent to handle separate SEC and ESEF taxonomies, the service maps concepts into a shared hub-code vocabulary. An agent can therefore request concepts such as revenue or total assets using the same code across issuers and filing regimes.
Returned facts include their filing source, reporting period, and provenance. The server is read-only: its tools advertise read-only, idempotent, non-destructive, and closed-world behavior. It does not provide database access or mutation operations.
The base tool set supports entity discovery by name, ticker, or CIK; concept lookup; standardized hub-catalog browsing; entity profiles; individual facts; metric histories; segment and geographic breakdowns; amendments; issuer comparisons; metric rollups; currency conversion; and company screening. Currency conversion uses ECB reference rates and can handle closing, average year-to-date, and average prior-year rate types.
The server exposes 19 tools, nine resources, eight analytical prompts, and a completion API for hub-code autocomplete. Resources include the hub catalog, category information, financial-statement guidance, entity profiles, tool-tier details, data-coverage information, and client usage guidance. Analytical prompt templates cover peer comparison, quality of earnings, restatement audits, sector overviews, valuation screening, goodwill impairment risk, working-capital diagnostics, and cash-flow consistency.
With Pro access, agents can inspect amendment differences, compare filings across periods, retrieve filing calculation trees, list issuer-specific extension concepts, obtain data-quality grades, and read XBRL validation results. Some base tools also have larger limits or deeper results with Pro access.
Install the Python package with pip install hub-equity-mcp and use Python 3.12 or newer. The Hub-Equity MCP MCP server is started as a stdio process with python -m hub_equity_mcp.server. Claude Desktop and Cursor configurations use this command and can pass environment variables to the process.
No key is needed for anonymous operation. Anonymous requests use the public REST API at https://api.hub-equity.com, provide the base tools, and are limited to 60 requests per minute per IP. Set HUBEQUITY_API_KEY to a hubq_ key for Pro tools; Pro and Enterprise plans raise the limit to 300 or 1000 requests per minute respectively. The key is free to create from a Hub-Equity account during beta, while paid plan availability is described separately.
HUBEQUITY_API_URL can override the default API endpoint. When a key is configured, HTTPS is enforced for non-loopback hosts so the bearer credential is not sent over plaintext. Before tool calls, client developers are advised to read hub-equity://prompts/best-practices and include its guidance in the client system prompt.
The published package communicates with the public REST API rather than a database, so Supabase or database credentials are not required. Anonymous and free-key usage is rate-limited to 60 requests per minute, and the client retries rate-limit responses with exponential backoff up to three times before raising RateLimitExceeded.
The package is described as a newly published Beta client even though the underlying data engine and REST API run in production. Pro-only tools and deeper query limits require a suitable key and plan. The available data also depends on the live dataset exposed by the API, whose coverage can be checked through the data-coverage resource.
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