"Retrieving information from document directory with search and memory capabilities" matching MCP servers:

Local, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates

Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.

Provides fully local, privacy-preserving semantic search over file names and paths via MCP, using BGE embeddings for fuzzy matching and supporting incremental updates, watch mode, and a loopback-only HTTP server.

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.

Minimal long-term memory MCP server for AI assistants backed by SQLite FTS5 full-text search, optional hybrid vector retrieval, scoped memory graphs, and VSCode extension.

Governed multi-agent memory for AI agents. Hybrid markdown + SQLite store with full-text search, vector retrieval, and LLM reranking. Three transports: MCP stdio, HTTP JSON-RPC, and MCP SSE. One Go binary

Manages an agent's long-term memories as versioned markdown files with searchable SQLite indexes, supporting lifecycle states, conflict-gated recall, revision, and explicit forgetting without automatic deletion.

Use Tavily Search to search for news pages or images.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.

Provides coding agents with persistent local memory by exposing tools to save, search, and retrieve decisions, bugs, and context as Markdown with hybrid keyword and semantic search.

MCP server that provides web search via LLM API gateways with server-side search, returning cited answers and multi-provider fallback.

An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.

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

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

Compare service-grant changes, tool alias origins, and saved MCP tool definitions with Gooo rules. Reports preserve incomplete-capture uncertainty and source bindings. No grants are applied and no compared tools are invoked.

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI.

Send email, find out why an email failed, set up sending domains, and manage templates, contacts, lists and campaigns in your AhaSend account.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

Enables searching and retrieving information from Slack messages, threads, files, canvases, and user profiles using a User Token, with advanced filtering capabilities.

Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.

Provides coding agents with real-time, code-aware functionality to locate relevant files and search code within a repository based on bug reports or queries.

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

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.

Go MCP server for multi-format document access — PDF, TXT, MD, DOCX, CSV, images. 12 tools including OCR, search, table extraction, and URL fetch. Single binary, no runtime.

Portable memory protocol for AI coding sessions. Push the state of a session (goal, decisions, attempts, next step) from one MCP-capable agent and pull it back from another.

MCP server for patent search and prior art discovery powered by Google Patents public dataset on BigQuery. Supports searching patents, fetching full patent details with CPC codes and citations, and retrieving legal claims text.

Persistent memory engine for AI coding agents. Single Go binary, zero runtime dependencies, MCP-native. Stores, searches, and deduplicates memories across sessions using embedded SQLite with hybrid FTS + semantic search, memory decay, relation graph, and token-budget context assembly.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.