"Enterprise-level Confluence search page supporting version 9.4.11" matching MCP servers:

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 Claude Code (or any MCP client) to run hybrid vector and keyword search over a locally indexed Confluence Data Center / Server instance, retrieve full page text, check index status, and trigger background refreshes.

Retrieves indexed Confluence pages via semantic search, returning chunks, citations, and page bundles; stores embeddings in local SQLite with sqlite-vec.

Enables stdio-capable MCP clients to run governed enterprise operations tasks, including policy/runbook retrieval and ticket and user lookups or writes. High-risk actions are held for human approval and role-based access is enforced server-side, so clients cannot bypass governance.

Enables querying enterprise documents (DOCX, PDF, PPTX) using natural language, with hybrid search and MCP integration for Claude Desktop and other agents.

A secure, multi-tenant Model Context Protocol server that gives AI clients controlled access to enterprise knowledge bases, SQL databases, REST APIs, files, and GitHub.

Enables retrieval of relevant context from Confluence pages using RAG and ChromaDB, integrating with code assistants like GitHub Copilot to enhance documentation queries.

Enables AI agents to securely search and ingest corporate documents via MCP, offering hybrid retrieval, PII sanitization, role-based access control, and citation validation.

Enables querying Confluence or Kubernetes documentation through hybrid search and an agentic RAG pipeline, returning structured answers with citations.

An MCP-based enterprise tools server that exposes company knowledge search and employee database lookup as callable tools.

Enables natural-language retrieval from enterprise policy documents via RAG, exposing search_enterprise_knowledge and get_document_sources tools.

Enables secure, stateful AI agents and LLM tools to access enterprise databases, knowledge bases, live system metrics, and sandboxed code execution through the Model Context Protocol, with authentication, rate limiting, and safety guards.

Enables natural language queries over internal policy documents using RAG, and provides tools to search policies and check ticket status via MCP.

Turns Confluence documentation into an AI-powered knowledge base, enabling natural language questions about your systems with answers retrieved from your actual documentation through semantic search.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

Hebbian learning MCP server with neural memory graphs, eligibility traces, and three-factor reward signals. Associative memory that strengthens through use.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

Enables natural-language querying of simulated HR data through a safety-gated MCP tool layer, routing questions to SQL or policy document retrieval with PII masking, role-based access, and an offline evaluation harness.

Provides hybrid search (BM25 + vector) and staleness reporting for local markdown notes, exposing search and indexing tools to AI assistants via MCP.

Free web search and page fetching for AI agents. No account or API key required. Connect to https://search.parallel.ai/mcp over Streamable HTTP. Tools: web_search and web_fetch. Free-tier rate limits apply.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.

Enables SDK and MCP clients to perform repository code search and retrieval, inspect current source and related evidence, and optionally use semantic search, reranking, and web sources while keeping the calling agent in control.

MCP server for searching files on macOS by name or content using semantic and lexical search, providing file paths and line numbers for agents to read from.

Multi-engine aggregated search MCP server that combines results from 7 search engines with deduplication, relevance ranking, and web page content extraction.

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