"Creating a Document as a Knowledge Base" matching MCP servers:

A local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.

Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.

Fetches documents by URL, DOI, ISBN, PMID or PMCID, and reports a block as a block, never as an empty success.

Your agents, briefed. Not flooded. Self-hosted context compiler: git-backed team knowledge served to coding agents as token-budgeted bundles over MCP.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

MCP server that indexes Markdown, Word, HTML, and PDF documents into a SQLite knowledge graph with CJK+Latin full-text search and cross-document reference tracking. Runs drift audits to surface stale policies, conflicting research claims, superseded ADRs, and undocumented code exports.

Persistent memory for AI agents as a single Go binary: hybrid recall, self-building knowledge graph, and a live TUI dashboard. Zero infra, offline-first — works with Claude Code, Cursor, Codex, OpenCode, and any MCP client.

Agent-native discussion forum for the x402 / A2A ecosystem. A hosted MCP server exposes the whole forum as tools (threads, comments, votes, bounties, reviews, search, profile) with x402 paid threads and USDC bounties on Base. Endpoint: https://api.achivx.com/mcp/

Serves offline document validation and evaluation operations of the Judgment Pack Specification to MCP clients over stdio, enabling agents to validate and evaluate JPS documents as tool calls. Supports conformance validation, experimental evaluation with disposition and error classes, and corpus testing.

Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.

Description: Introduce Beelzebub, an MCP‑based honeypot framework that enables creating decoy tools to detect prompt injection and malicious agent behavior. Motivation: Strengthen the security of LLM workflows by adding a non‑intrusive detection mechanism.

Enables AI assistants to interact with MAAS (Metal as a Service) infrastructure for machine management, network configuration, and storage management through a standardized JSON-RPC 2.0 interface.

KSM MCP is a Model Context Protocol (MCP) server that acts as a secure intermediary between AI language models (like Claude) and Keeper Secrets Manager (KSM). It allows AI agents to manage your KSM secrets-such as listing, creating, retrieving, and deleting records and folders-while protecting your

A lightweight, zero-agent SSH operations tool that enables remote command execution, file transfer, and audit logging. It integrates as an MCP server for AI-driven infrastructure management.

A modern community hub with forum and knowledge base. Native MCP built-in, ready for the next era of internet culture.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

A frontier knowledge base that’s minimal extensible and agent-native. Built to keep your team’s shared context current and inspectable.

Enables AI agents to orchestrate 100+ security tools over MCP for authorized penetration testing, including recon, scanning, exploitation, attack-chain planning, and knowledge-base retrieval.

A self-hosted personal context server that unifies knowledge base, retrieval, credential management, and agent memory via MCP, with a built-in notes app for human oversight.

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.