"How to run Python code" matching MCP servers:

Read-only Python MCP server for TA-Lib indicator discovery and computation.

A Node.js MCP server that provides tools for interacting with the Sienge API, covering modules like nucleus, cadastros, and compras with parity validation against the Python version.

Enables generating Python code for Meritz Securities Open API calls, including API search, detail retrieval, and code generation, without requiring an app key.

Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.

Paybond Kit for Python is the PyPI package for tenant-bound Paybond integrations and delegated agent spend controls. It opens hosted Gateway sessions, verifies capability tokens, authorizes tool-call spend, signs intent and evidence payloads, uses Stripe Connect, Stripe ACH Direct Debit, or x402 / USDC-on-Base settlement rails, reads tenant-scoped Signal, fraud, ledger, protocol, and A2A data, and

Enables MCP-compatible AI agents to access Polymarket prediction-market data and run Python 3.12 in an isolated sandbox, with each call paid automatically in USDC on Base.

Enables MCP clients to run live web searches, fetch and navigate readable web pages, search images, capture PDF screenshots, and retrieve finance, weather, sports, and world-time data through a zero-configuration authenticated backend.

Enables MCP-compatible LLM clients to interact with IBM Planning Analytics/TM1 models through callable tools, supporting read operations like inspecting cubes, dimensions, and MDX queries, plus write/model-building operations in read/write mode.

MCP server exposing a parametric policy engine for evaluating, simulating, and managing rules, with dynamic plugin support for domain-specific calculations.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

A simple MCP server that exposes stock price lookup tools, demonstrating how to set up MCP from scratch with Ollama.

A minimal Python MCP server over Streamable HTTP using FastAPI, exposing demo tools like ping, get_positions, and list_upcoming_corporate_actions that can be replaced with read-only adapters to custody data.

MCP server for cove-fi, a deterministic retirement and financial-independence projection engine. It lets users run plans, create scenarios, and explore year-by-year net-worth projections through natural language.

AI-powered expense tracking MCP server that connects LLM clients to PostgreSQL for natural language expense management.

Enables managing personal expenses through MCP tools for registering and listing gastos, reusing the backend's service layer.

Enables AI agents to query US public company financial data from SEC filings, with tools for resolving tickers, listing filings, retrieving financial concepts, comparing companies, extracting filing sections, and full-text search. It surfaces data ambiguities like tag variations, restatements, and fiscal-year misalignment rather than hiding them.

Provides read-only tools to query live Polymarket prediction-market data via the public Gamma API, enabling search, browsing, and detailed market and event information.

Read-only SQL MCP server for quantitative finance data (DuckDB) with stock quotes, financials, and historical K-lines, enabling cross-database JOIN queries.

Brazilian foreign trade from MDIC/ComexStat -- exports and imports since 2000 by HS code (SH4/SH6/NCM) and partner country, in USD FOB and kilograms -- plus crop production, supply-and-demand balances, climate readings and commodity forecasts for hubs such as soybean, coffee and beef. 15 read-only tools, remote at https://mcp.kyrodata.com/mcp; official registry com.kyrodata/kyrodata.

Enables LLM agents to retrieve normalized US-GAAP financial statements from SEC EDGAR—income statement, balance sheet, and cash flow—with point-in-time as-reported figures and per-value SEC source provenance for citation.