"Python runner with streamable HTTP support" matching MCP servers:

A step-by-step guide and complete working example for building and running an MCP server with streamable HTTP transport using Python, mcp, and FastAPI, enabling AI assistants to access tools over HTTP.

A bridge server that converts stdio protocol to streamable-http protocol, allowing clients to interact with MCP services over HTTP.

Enables exposing MCP tools over HTTP using Python and FastAPI, allowing AI assistants like Cursor to connect and use tools like web search, echo, and math operations.

Demonstrates building an MCP server with Python, exposing tools like web search (Tavily) and basic utilities over streamable HTTP for AI assistants like Cursor.

A Python-based MCP server that exposes tools over streamable HTTP using FastAPI, enabling connection to AI assistants like Cursor. Supports multiple servers mounted in a single FastAPI app.

A minimal Model Context Protocol server that facilitates network-based client connections using Streamable HTTP transport. It provides a greeting tool and is optimized for consistent deployment across local environments, Docker, and Kubernetes.

Provides basic arithmetic calculation tools through an HTTP-accessible MCP server. Supports mathematical operations like addition with streamable responses for integration with MCP clients.

Enables remote server control via SSH through Claude, supporting command execution, file transfers, and multi-server management with both standard and streamable HTTP protocols.

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.

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.

Bridges STDIO MCP clients to Streamable HTTP MCP servers, allowing any STDIO-supported client to use Streamable HTTP servers immediately.

A Docker-based deployment that wraps the Gemini MCP server with supergateway to expose its tool capabilities over Streamable HTTP. It enables users to perform image-editing workflows and interact with the Google Gemini API using a standardized web-accessible endpoint.

A starting template for building a Streamable HTTP MCP server using TypeScript, based on the official SDK example with session management.

Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.

A transport wrapper that exposes Contentstack MCP tools over HTTP instead of stdio to enable remote access and horizontal scaling. It acts as a proxy for the Contentstack MCP package, allowing browser-based and networked clients to interact with various Contentstack APIs.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

Enables an ElevenLabs support agent to call support tools over MCP, including Discord ticket flows, post-call webhook handling, and knowledge-base syncing.

Enables fetching HTTP resources through the MCP protocol.

A TypeScript boilerplate for building Model Context Protocol servers using the Streamable HTTP transport and session management. It serves as a foundational template with pre-configured development tools to help developers quickly build and deploy streamable MCP services.