"Information about agents or agent-related topics" matching MCP servers:

Local MCP server for specialist personas, reusable Markdown workflows, task-scoped subagent contracts and per-repository memory. Runs on your own computer with Python 3.11+ and a locally installed embedding model; its Claude Code plugin launches that separate installation.

Evidence-governed coding agent memory and knowledge lifecycle MCP server for DeepSeek Harness (DSH), OpenAI Codex, and Google Antigravity. Provides local SQLite FTS5 + semantic hybrid retrieval, automatic session/compaction checkpointing, counter-example demotion, and a hard 1,200-char context budget guardrail with zero third-party Python dependencies.

A multi-agent product-management copilot that automates morning briefings, metrics answers, knowledge lookups over an Obsidian vault, and PRD/ticket drafting.

A Model Context Protocol server that enables Claude users to access specialized OpenAI agents (web search, file search, computer actions) and a multi-agent orchestrator through the MCP protocol.

An MCP server that runs AI-driven venture capitalist agents whose thinking is continuously enriched by Octagon Private Markets' real-time deals and intelligence for pitch feedback, diligence simulations, and term sheet negotiations.

A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Enables travel-related queries and planning including weather, train and flight information, itinerary generation, and travel knowledge retrieval via RAG, using an AI agent with MCP protocol.

A self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.

Exposes tools that let an agent search a local Markdown-based memory store, fetch full cards by id, write new knowledge cards that are indexed immediately, and inspect or rebuild the SQLite index. All retrieval runs locally over Chinese-friendly full-text search with graded exact/prefix matching, so agents without a memory system can recall prior notes while existing Markdown files stay read-only.

A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).

A provider-neutral MCP server that provides tools for managing skills, agents, references, and artifact memory in a local workspace.

Enables AI agents to discover and query enterprise knowledge documents and business metrics through standardized MCP tools, supporting retrieval, structured sales/order analysis, anomaly scanning, and data lineage lookups.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

Enables cross-session memory and recall for AI coding assistants through a git-synced knowledge base, hybrid semantic and TF-IDF search across tool transcripts, and automatic distillation of insights with secrets scrubbing.

Long-term memory for AI agents. Compiles conversations into a structured knowledge base with Claim/Evidence model, source provenance, append-only timeline, and contradiction detection. Multi-path retrieval (Exact + BM25 + Graph + weighted RRF + reranker) — 96.6% R@5 on LongMemEval-S, zero vector dependencies.

Shared knowledge graph for AI coding agents. Search, create, and link verified technical knowledge across 12 node types with trust scoring, demand signals, and auto-provisioning. Install: npx agent-hive-mcp

A Model Context Protocol (MCP) server that enables integration of Strands agents with Amazon Q and other MCP-compatible systems through a plugin architecture.

Exposes a personalized AI agent that reads your resume and provides intelligent responses about your professional background through a standardized MCP server interface with RAG capabilities.

Publishes an MCP server that lets other AI agents browse a project's unified cross-agent session archive: list projects, view timelines, run full-text searches, read existing digests and session summaries, read session bodies in bounded chunks, check collection stats, and export Markdown. All tools are read-only and truncate long output so callers can decide whether to read further.

Enables AI agents to persist and recall episodic memories across sessions, consolidating experiences into reusable rules and lessons to reduce repeated mistakes and improve task performance.

Serves a site's validated public profile, product list and newest-first posts to AI agents through three read-only tools (get_profile, list_products, list_posts) over stdio or any Web Request/Response runtime.

Enables AI agents to run reproducible, high-recall literature search across seven source families with RRF fusion, fetch open-access full texts (falling back to abstracts), expand citations, export BibTeX/RIS, and audit reference coverage — all without any LLM API key, leaving query planning and writing to the agent. Multiple agent clients share one accumulating literature pool and background search jobs that keep running after sessions close.

Archive Agent is an open-source semantic file tracker with OCR + AI search (RAG) and MCP capability.

A self-hosted, MCP-native web-search backend for AI agents that provides meta-search, clean extraction, RAG with citations, and GitHub project selection.

Enables AI agents to search a local Obsidian knowledge base, retrieve individual notes, and access generated insights through read-only MCP tools.

Provides persistent cross-session memory for Claude Code, enabling it to remember user preferences, decisions, and project context across new sessions.

A multi-function Streamable HTTP MCP tool aggregation server that provides web search via Brave, Exa, and SearXNG with multi-key rotation and cross-provider fallback, and supports extensible tool families (URL fetch, code search, RAG) through a pluggable architecture.

Enables AI agents to keep and query long-term memory of past conversations, with hybrid keyword-plus-semantic search, session, day, week, month and year summaries, saved notes, and a running set of current facts about the user. Exposes this over MCP streamable HTTP through five tools so any client can retrieve context that would otherwise be lost between sessions.

Exposes tools for AI agents to check the connected object store's source and index status, and to search a synced bucket prefix for source-backed chunks using keyword, vector, or hybrid retrieval. Results include source URI, chunk and score so citations can be preserved.