A server that helps people access and query data in databases using the Legion Query Runner with Model Context Protocol (MCP) in Python.

🦜✨ Chat system, MCP server, and reusable components to improve LLMs capabilities when generating SPARQL queries

Query and Summarize your chat messages.

Enable AI assistants to explore and query your Steampipe data!

BloodHound-MCP-AI is integration that connects BloodHound with AI through Model Context Protocol, allowing security professionals to analyze Active Directory attack paths using natural language instead of complex Cypher queries.

A Model Context Protocol (MCP) for analyzing and querying GitHub repositories using the GitHub Chat API.

An MCP server for querying Solana transactions using natural language with Solscan API

An MCP server to query any Postgres database in natural language.

MCP server for querying Apple Health data with natural language using DuckDB under the hood.

A Model Context Protocol (MCP) server that provides access to your TeslaMate database, allowing AI assistants to query Tesla vehicle data and analytics.

LLM-compiled knowledge bases for any AI agent. Parallel multi-agent research, thesis-driven investigation, source ingestion, wiki compilation, querying, and artifact generation.

A Model Context Protocol (MCP) server for Langfuse, enabling AI agents to query Langfuse trace data for enhanced debugging and observability

Graph-vector database that queried 1 billion edges for $2.50. Rust, OpenCypher, vector search, 14 graph algorithms. 74M nodes / 1B edges on a single machine.

Write detections, investigate alerts, and query logs from your favorite AI agents

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

🤖 Curated AI OSINT resources — Google dorks, Shodan queries, GitHub dorks, and techniques to discover exposed LLM endpoints, leaked AI API keys, misconfigured vector databases, and unprotected AI agents

A Model Context Protocol server that connects AI assistants like Claude to AWS security services, allowing them to autonomously query, inspect, and analyze AWS infrastructure for security issues and misconfigurations.

📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev

Free, maintained Python library + CLI for Google Trends: trending now, plus keyword interest over time, related queries & interest by region. A modern pytrends alternative.

Official Findings of EMNLP 2026 implementation of Corpus2Skill: compile a document corpus into a navigable skill hierarchy that LLM agents explore at query time, with document lookup instead of a serving-time vector-search service.

Local-first AI memory MCP server — query your ChatGPT, Claude Code, Cursor & Codex history from any LLM. DuckDB+parquet.

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

AI-native ontology engine: a Rust MCP server with tools for building, validating, querying, and reasoning over RDF/OWL ontologies. In-memory Oxigraph triple store, native OWL2-DL tableaux reasoner, SHACL validation, SPARQL, versioning. Single binary, no JVM.

Own your LLM's web search: a local search->fetch->rank pipeline that replaces hosted web-search tools. Measured: matches hosted accuracy at 66% lower cost and up to 88% fewer tokens, plus a precision-tuned semantic caching with query-dependant TTL that no API offers.