"John Deere" matching MCP servers:

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Provides an LLM agent with extreme value statistics tools for tail risk analysis, including peaks-over-threshold GPD fitting, VaR and Expected Shortfall estimation, return levels, threshold-stability diagnostics, and out-of-sample VaR backtesting.

Connects MCP-compatible clients to an already-deployed DeerFlow instance over its HTTP API, exposing deep research runs, model listing, and thread, run, and artifact control as callable tools. It acts as a thin stateless adapter, so clients can launch cited research reports and manage DeerFlow workflows without running the backend themselves.

A Model Context Protocol server providing durable, cross-session memory for AI agents, powered by Qwen on Alibaba Cloud. Enables agents to write, search, recall, and forget memories with semantic ranking.

An MCP server implementing Spec-Driven Development workflows for AI-agent CLIs and IDEs like Claude Code and Cursor, enabling spec-first development with automated workflow guidance and quality checks.

Enables professional penetration testers to run reconnaissance, exploitation, brute-force, and credential-cracking tooling (nmap, gobuster, nikto, John the Ripper, hashcat, subfinder, httpx, ffuf, nuclei, hydra, sqlmap, tcpdump) through MCP clients over stdio or HTTP. It also captures engagement records and generates client reports with scope-of-work handling and bearer/OIDC authentication.

Enables professional penetration testers to drive recon and exploitation tooling — including nmap, gobuster, nikto, John the Ripper, hashcat, subfinder, ffuf, nuclei, hydra, and sqlmap — over stdio, Streamable HTTP, or SSE transports with bearer/OIDC auth. Also supports wordlist generation, engagement record capture, and automated client report creation with scope-of-work handling.

Validates legal citations against the CourtListener database to detect hallucinated citations in legal documents.

Provides contextual Oracle database schema information to AI assistants, enabling them to understand and work with large databases containing thousands of tables. Supports multi-database connections, smart schema caching, table lookups, and relationship mapping.

A production-ready starter template for building Model Context Protocol (MCP) servers with TypeScript. Includes automated tooling for creating new MCP tools, testing, and deployment to Claude Desktop.