"A tool for analyzing Python repository structure and code relationships" matching MCP servers:

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

A Model Context Protocol server that extracts and analyzes Python code structures, focusing on import/export relationships between files to help LLMs understand code context.

Run free live audience Q&A and polls from your agent: start an AskOne room, add and launch a poll, approve or hide questions and mark them answered, close the room, then read the questions as a FAQ draft and get the results. Free AI moderation. Uses an organization API token from askone.org

Python Docs MCP Server gives AI coding agents local access to the official Python standard library docs. It can look up docs by Python version, return specific sections, and keep answers compact for clients like Claude Desktop, Cursor, and Codex. It runs without API keys or a hosted service.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables AI assistants to analyze smart-money market structure—trend, character shifts (ChoCh/BOS), liquidity sweeps, fair value gaps, order blocks, and pullback zones—from Hyperliquid or user-supplied candles.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.

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

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

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

MCP server for GitHub code retrieval and reuse, using SQLite+FTS5 indexing and search history to enable search-first, requirements-refined code search from GitHub repositories.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.