"Multi-platform information search across productivity and knowledge tools" matching MCP servers:

Provides unified web search across multiple providers (Google, Tavily, DuckDuckGo, Brave) with automatic fallback, maximizing free API quota usage for AI workflows.

Enables fast local hybrid search over a folder of markdown files via MCP, combining BM25 and vector similarity with explicit relevance verdicts and no LLM or network calls at query time.

Enables governed, read-only SQL analytics, hybrid RAG knowledge search, financial metric calculation, and database schema introspection through MCP, with role-based access control, audit logging, and AI observability.

Enables AI assistants to retrieve, search, and compare procurement documents using hybrid retrieval and MCP integration.

Vendor-neutral MCP server for knowledge retrieval across repositories, offering stable tools for searching, getting, and listing documents with hybrid lexical and optional semantic search.

Lets an AI assistant search, read, and write notes and sources in your self-hosted Open Notebook, with approval-gated writes and no data sent anywhere else. It bundles tools, prompts, and skills for meeting notes, decision records, weekly reviews, and source-cited research.

Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

Enables code agents to persist and recall durable project knowledge — rules, decisions, procedures, learnings and secrets — across sessions at low context cost, with accent-insensitive PT-BR search, scoped per repository/workspace, and secrets that stay out of the model's context.

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.

A self-hosted, MIT-licensed MCP server that securely connects private documents and markdown files to LLMs. It provides a lightweight, local-first RAG infrastructure compatible with any MCP-enabled AI client or framework.

Local knowledge engine for codebases with hybrid search, knowledge graph, and interaction tracking, enabling Claude Code to search and interact with project knowledge locally.

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.

Enables evidence-based retrieval across official BMC Helix product documentation and isolated private project knowledge, with product, version, project, source, and section provenance. Supports version-aware multi-product indexing, hybrid lexical and optional semantic search, and read-only access to local evidence without touching live Helix systems.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

A read-only MCP server that enables AI clients to search a knowledge base and retrieve complete source documents via narrow search and fetch tools.

An MCP-native evidence retrieval platform that ingests source material, builds lexical and vector indexes, performs hybrid retrieval, and returns structured evidence packages for AI assistants.

An MCP server that enables semantic search over a private knowledge base via pgvector, with GitHub OAuth authentication and a RAG pipeline.

Enables AI agents and MCP clients to search, retrieve, and read documents across unified knowledge sources including ShowDoc, GitHub, Gitee, ZenTao, Evernote, and Tencent Docs. It also supports connecting external MCP servers as additional knowledge sources.

Enables AI agents to capture, classify, synthesize, and retrieve shared persistent knowledge across sessions via MCP, with tiered memory, full-text and semantic search, and token-efficient context briefings.

Provides enterprise knowledge management capabilities via MCP, enabling semantic search across the knowledge base, retrieval of full documents by ID, and search over enterprise project cases.

Enables agents to retrieve permission-filtered document knowledge across organizations and knowledge bases, and to identify and expand business terms and typed object relationships through a unified MCP interface.

Enables AI agents to search, read, create, and maintain a local-first knowledge base using hybrid retrieval and Markdown note management through the Model Context Protocol.

A persistent memory system that captures, classifies, synthesizes, and retrieves knowledge for AI agents, turning raw information into refined, retrievable knowledge that compounds intelligence over time.

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 share a persistent, self-improving memory by ingesting sources such as Obsidian vaults, code, transcripts, and bookmarks, then classifying, promoting, synthesizing, and retrieving that knowledge through token-optimized search across MCP and REST interfaces. Agents can capture sessions and fixes so context compounds across sessions and across Claude, Codex, Gemini, and any other MCP client.

Enables agents to perform federated cited search and heuristic grounding across a governed versioned wiki and indexed files, inspect citation spans, and read or write scoped knowledge through HTTP or stdio MCP.

Enables LLMs to search and retrieve information from large technical documentation (OpenAPI specs, markdown) via intelligent chunking and semantic search.

This server enables AI assistants (CLINE, Cursor, Windsurf, Claude Desktop) to share a common knowledge base through Retrieval Augmented Generation (RAG), providing consistent information access across multiple tools.

An MCP server that enables AI agents to query specialized, domain-specific knowledge bases built using the LightRAG framework for enhanced retrieval-augmented generation. It allows for managing and searching knowledge graphs and vector embeddings to provide accurate, context-aware information during an AI assistant's reasoning process.