"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 router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

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.

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.

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.

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 declaring a catalog of tools for LLMs, filtering them by role, validating arguments, guarding sensitive calls with server-side confirmations, and recording an audit log.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

Routes external MCP tools behind a small on-demand discovery interface for Codex agents, using Jev to select relevant tools and providing fallback to the full inventory when confidence is low.

Enables locally configured MCP servers to be called over stdio and mixed with xAI server-side tools, without relying on hosted xAI MCP.

Enables AI agents to validate AI infrastructure claims, check endpoint availability, solve CAPTCHA challenges, convert web pages to Markdown, search the web, extract structured JSON, and fetch bot-protected HTML through native tool calls.

Enables agents to search across the pooled tools of many connected MCP servers and invoke them through a single endpoint, returning only the handful of tools relevant to each request. Filters by the caller's permissions before ranking, so agents never see or plan around tools their user is not allowed to use.

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.

Lets a human review what an AI agent is about to post to a chat tool (Slack first) before it is sent. Renders the draft, destination and warnings (@here/@channel, unresolved mentions, format issues) in a neutral local HTML preview; never sends anything.

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.

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.

Signed, offline-verifiable authorization for API-contract changes. Before a contract change (OpenAPI, GraphQL, Protobuf, AsyncAPI, MCP manifests) merges or deploys, the agent calls preflight_change_set; the decision is deterministic, signed, and verifiable without calling CodeRifts. Three tools: preflight_change_set, verify_receipt, get_decision_details. Only a granted change can proceed.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Lets AI agents drive a headless Chromium browser to open URLs, click, type, select options, read text/HTML, evaluate JavaScript, wait for elements, and capture real PNG screenshots. A persistent single session keeps cookies and SSO state across tool calls, and an optional live view mirrors pages in VS Code's integrated browser tab.

Exposes configured language models as ordinary MCP tools, enabling a host agent to select a model, send explicit message lists, and receive normalized responses through provider-neutral OpenAI-compatible, Anthropic, and Gemini adapters.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Enables MCP clients to browse a live catalog of 100+ models with pricing, rankings and measured uptime, check credits and spend, and send chat completions through an OAuth-authenticated, per-connection key capped by a spend limit. Read tools are free, and paid calls are priced and approved before any credit is used.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Exposes AgentHansa's MCP tools to remote clients over Streamable HTTP, enabling ChatGPT and desktop agents to use the AgentHansa service through a secure authenticated endpoint.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

Exposes any stdio-based MCP server to the internet via HTTP/SSE transport, enabling remote agents to access MCP tools over a network.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

Enables AI agents to open URLs in a persistent headless browser and interact with pages by clicking, typing, selecting, reading content, evaluating JavaScript, waiting for elements, and capturing screenshots.

Enables PraisonAI agents to solve authorized CAPTCHA challenges with a bounded one-attempt budget, structured result validation, and a human-review stop for denied, unsupported, exhausted, or malformed requests.