"Querying Elasticsearch (ES)" matching MCP servers:

A Model Context Protocol server that enables AI agents to dynamically interact with Hasura GraphQL endpoints through natural language, supporting schema discovery, data querying/manipulation, and aggregations.

A bridge that enables AI assistants to connect to VS Code's debugger, allowing them to interact with and control debugging sessions through websocket connections.

A Model Context Protocol server for JavaScript/TypeScript development, providing tools to run scripts, tests, builds, and dependency management with framework and package manager detection.

Provides a persistent Python REPL session as a tool for executing code, managing files, installing packages, and initializing projects via the MCP protocol.

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

Facilitates interaction with Microsoft SQL Server Express, supporting database operations such as querying, table management, and schema inspection via natural language MCP commands.

A comprehensive implementation of Model Context Protocol servers enabling natural language interactions with security platforms including Splunk SIEM, CrowdStrike EDR, and Microsoft MISP for threat intelligence querying and analysis.

Enables MCP-capable AI agents to work on bounded project folders through read, write, run, and verify tools, with durable approval/resume workflows and completion proven by observed verification evidence rather than self-reported results.

Enables full control database operations on MySQL through natural language commands. Supports querying, data manipulation, table management, backups, and system administration with comprehensive SQL execution capabilities.

Aggregates tools from multiple MCP servers, generates TypeScript definitions, and executes custom TypeScript scripts to orchestrate cross-server tool calls.

An MCP server for managing ESP-IDF workflows, enabling LLMs to build, flash, and test firmware for ESP32 and related microcontrollers. It provides tools for project creation, target configuration, and serial port management to simplify embedded development.

Enables interacting with a DuckDB database through MCP tools for SQL querying, table creation, and schema inspection, with optional read-only enforcement.

A FastMCP server that enables natural language querying of PostgreSQL databases through LLM integration, allowing users to generate SQL queries from plain English and visualize the results.

Enables AI assistants to control Houdini by executing Python code, querying scene information, and creating nodes via the Model Context Protocol.

Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

Connects MCP clients to a local Blender + Bonsai (BlenderBIM) session for scene inspection, IFC project querying, viewport screenshots, and executing Python code in Blender.

Enables AI agents to write, validate, and render high-quality PostScript by providing operator lookup, vetted PSlib fragments, cited reference search, and Ghostscript-based checking.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.