"Python context management and dependency solving in ComfyUI" matching MCP servers:

A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.

A simple MCP server that can enable MCP clients to query Bluesky instances.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

An MCP server that enables interaction with Google's My Business Account Management API, allowing users to perform account management operations through natural language interactions.

An MCP server that enables management of Google Play games via the Google Games Management API, allowing automated interactions for game resets, hiding/unhiding data, and player management through natural language commands.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

A Python server implementing the Model Context Protocol that exposes tools for querying external APIs, compatible with Claude Desktop and ChatGPT Desktop.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Official MCP (Model Context Protocol) server for Iron.xyz API, designed to work with Claude Desktop, Cursor IDE and other MCP compatible clients.

MCP server for reading, writing, and organizing API documentation in Apidog.

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

An MCP server for Tern that enables the generation, verification, and management of webhook handlers across over 16 platforms and various frameworks. It provides tools to create verified endpoints, debug signature failures, and manage failed event replays via dead letter queues.

Enables AI assistants to interact with Fastly's CDN API through the Model Context Protocol, allowing secure management of CDN services, caching, security settings, and performance monitoring without exposing API keys.

Runs, tests and edits the saved HTTP requests in a Kurlo API workspace (Git-backed YAML): list collections and environments, send requests with their auth and pm.* tests, write new requests and tests, and diagnose the last failure. Secret values are sent to the API but masked in every tool result, and protected environments are refused.

An MCP server that generates MCP servers. Give it an API definition - OpenAPI 3.0/3.1 or a Postman collection or extend an existing server - and it scaffolds a complete, runnable, ownable TypeScript or Python MCP server for that collection of APIs.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.

A Model Context Protocol server enabling AI assistants to interact with Kong Konnect's API Gateway, providing tools to query analytics data, inspect configurations, and manage control planes through natural language.

A small native HTTP client whose MCP server (plunger mcp) lets an AI agent send requests safely: undefined variables are refused, secrets are filled in by name and masked in results, and every request is recorded in a history you can see in the window. MIT licensed, for Windows, with a Linux build of the CLI and MCP server.

Python MCP server for running and inspecting Bruno API collections

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.