"Information about GraphQL" matching MCP servers:

Self-hosted, open-source (AGPL-3.0) MCP gateway that turns REST, SOAP/WSDL, GraphQL, and SQL/NoSQL databases into MCP tools. Imports OpenAPI/Postman/WSDL/GraphQL specs and bridges multiple MCP servers behind one endpoint. Ships 188 pre-built adapters, 26 of which need no API key, plus per-tool response mapping, OAuth2/RBAC/SSO and a full audit log.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

Turn your existing REST, GraphQL, and gRPC APIs into governed, AI-native MCP tools with reShapr. Enable AI agents to interact with your APIs through discoverable, reusable tools, with control over tool exposure and context, to build more reliable, efficient agentic workflows.

Enables AI agents to connect to any API by loading OpenAPI, GraphQL, gRPC, or SOAP specs, with a built-in catalog of 2500+ public APIs, supporting secure execution, response filtering, chaining, and parallel calls.

Enables creating and running production-grade Model Context Protocol servers for REST APIs, GraphQL endpoints, OpenAPI specs, Google Cloud services, and custom Python logic from a declarative JSON blueprint, with built-in authentication, response shaping, multiple transports, and one-command Cloud Run deployment.

An autonomous Go MCP server that dynamically imports OpenAPI, GraphQL, and AsyncAPI specs and exposes them as tools to agents with self-learning and auto-documentation.

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

A transparent message ferry between Claude Desktop and Claude Code CLI, enabling task delegation with any MCP configuration without the bridge needing to know about specific MCPs.

Universal MCP router and gateway that bridges LLM agents to OpenAPI, GraphQL, and AWS Lambda services with ISO/IEC 42001 AI governance, RBAC, PII redaction, semantic tool routing, and a web dashboard.

Enables AI agents to query the Idira (CyberArk) Discovery & Context inventory and to add, replace, or delete secrets, machine identities (workloads), and AI agents through the GraphQL API. It runs as a remote OAuth 2.1 protected resource so it can sit behind the Idira Agent Identity Broker, with every tool call authorized and audited.

An integration layer for AI agents that provides a catalog of tools from various sources (OpenAPI, GraphQL, MCP, etc.) and can be used as an MCP server for compatible agents.

Turns any REST/OpenAPI, SOAP, GraphQL, OData, SQL, MongoDB or existing MCP system into MCP tools for Claude, ChatGPT and Copilot without writing an MCP server, shipping 474 ready-made connectors with runtime tool registration, field filtering and role-based access control.

Enables Cursor agents to communicate via a shared chat room, allowing them to ask questions, share status, and warn about conflicts while collaborating on the same repo.

Enables read-only access to Pocket Agent's product information, public persona templates, and app catalog. No authentication required.

Enables AI agents to access a unified catalog of tools from various APIs (OpenAPI, GraphQL, MCP, Google Discovery) through the MCP protocol.

Enables AI models to access user geolocation information through EdgeOne Pages Functions, allowing location-aware AI interactions.

A Server-Sent Events implementation using FastAPI framework that integrates Model Context Protocol (MCP), allowing AI models to access external tools and data sources like weather information.

MCP server that enables Claude Code to communicate with other Claude Code agents over HTTP, allowing users to ask questions about remote codebases or delegate coding tasks.

Enables AI agents to discover, compose, execute, and persist capabilities from OpenAPI, GraphQL, MCP servers, web forms, and peer runtimes through one MCP connection. It lets successful multi-provider workflows be saved as reusable endpoints and automatically re-planned when upstream contracts change.

An interface enabling high-frequency communication between AI tools (like Cursor and Windsurf) and users, allowing for option selection and information gathering through CLI, Web, or PyQt interfaces.

An MCP Server that provides weather information by ZIP code using Interzoid's API, allowing agents to retrieve current weather conditions based on postal codes.

Enables interaction with a TrueRAG system through a GraphQL API using the Model Context Protocol (MCP), facilitating access to policies with a Python SDK and GQL library integration.

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.

A server that allows AI agents to consult multiple large language models (like Grok, Gemini, Claude, GPT-4o) through Model Context Protocol for assistance and information.

An MCP (Multi-Agent Conversation Protocol) Server that provides an interface to access Pokémon data through the PokéAPI, enabling agents to retrieve information about Pokémon species, abilities, moves, and more via natural language.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.