"Automating HTTP API Wrapping into MCPT Tool" matching MCP servers:

Provides an HTTP API for Claude Code using a native MCP channel to enable stable message exchange without terminal screen-scraping. It allows users to programmatically send messages, retrieve conversation history, and stream real-time events via standard web protocols.

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.

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.

Transforms stdio-based task tools into a stateful Streamable HTTP MCP server, enabling multiple clients to manage tasks via URL with session isolation and security checks.

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.

An MCP server providing risk-aware API governance tools for AI agents. Agents call preflight checks before tool calls or merges to verify API contracts are safe. Returns risk score, blast radius, agent impact, economic cost, and a deterministic ALLOW/WARN/REQUIRE_APPROVAL/BLOCK decision. MCP endpoint: https://app.coderifts.com/mcp

Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.

Proxies STDIO-based MCP clients to streaming HTTP MCP servers, enabling local clients to connect to remote servers.

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.

Provides pre-fetch routing intelligence for AI agents by recommending the cheapest reliable route (HTTP, browser, machine endpoint, or avoid) before visiting a URL.

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.

Bridges stdio Model Context Protocol (MCP) servers to MCP Streamable HTTP behind a single gateway, enabling multi-tenant, multi-user deployment with per-tenant environment variables via HTTP headers.

Provides full Devin API coverage via MCP servers, enabling programmatic management of sessions, knowledge, playbooks, secrets, schedules, and attachments, plus a documentation-only DeepWiki proxy.

A meta API Gateway server that works with the Model Context Protocol (MCP), enabling AI assistants to connect to any API and access real-world data sources through standardized MCP tools.