"A tool for retrieving Python library documentation" matching MCP servers:

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

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

A configurable MCP gateway that runs multiple Streamable HTTP MCP servers and exposes all their tools through a single endpoint, enabling tool aggregation and routing for MCP clients.

A framework for building hot-loadable MCP tools that feature conversational negotiation, graduated permissions, and zero-downtime updates. It enables persistent state continuity across server restarts and provides a hypothetical evaluation system for tool actions.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

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.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.

Enables developers to build and deploy secure, typed Model Context Protocol servers with tools, resources, prompts, bearer-token authentication, per-tool scopes, rate limiting, and health probes over Streamable HTTP.

Enables AI agents to securely discover, invoke, and manage tools through a hardened MCP endpoint with protections like injection detection, circuit breakers, retry backoff, response caching, context-window limiting, and state snapshots.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.

A generic MCP proxy that filters which tools are exposed from a remote MCP server, reducing context window token usage by only loading the tools you actually need.

Reference implementation of a Model Context Protocol server for integrating external APIs as agent tools. Includes built-in tools for weather, database queries, web search, and calculations, with authentication, rate limiting, and logging.

A demonstration server implementing the Model Context Protocol with Server-Sent Events for streaming content production and management.

Enables AI agents to drive real Google Chrome with stealth and captcha handling, using Patchright to avoid bot detection.

Enables access to agent instruction files and prompts for AI development workflows. Provides tools to retrieve and list development rules, security checks, and common prompts from an agents library through MCP protocol.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.