"Integrating corporate Confluence with model access for search and document navigation" matching MCP servers:

MCP server for integrating Confluence with AI agents, enabling search, read, and retrieval of documentation, plus syncing and pushing markdown files.

Local-first MCP server for navigating and maintaining arbitrary hierarchical documentation with flexible node structure, raw content, and multiple parents, leaving navigation decisions to the connected LLM.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Enables AI interaction with Microsoft Access and SQLite databases to perform SQL queries, updates, and data management. It supports importing and exporting data via CSV and Excel files and includes tools for managing human-readable notes about database files.

A local MCP server providing read-only access to documents like Word, PDF, Excel, and images, with file listing, reading, and metadata extraction.

Enables querying corporate knowledge such as HR policies, vendor contracts, and support FAQs, with every answer grounded in an exact source and retrieval quality and hallucination rate explicitly measured.

A minimal MCP server providing a normalized API for code navigation and repository inspection through tools like symbol searching and call tracing. It enables AI agents to perform structured analysis of codebases by mapping endpoints, inspecting file trees, and tracing symbol relationships.

Enables MCP clients to read, search, and manage a Yahoo Mail mailbox over IMAP and send or forward messages over SMTP, with multiple accounts selectable per call and writes defaulting to drafts, trash, or dry-runs until explicitly confirmed.

An MCP server that exposes documents.js's document conversion, .odb, metadata, and font tooling as MCP tools, enabling agents to convert, inspect, and edit a wide range of document formats over stdio.

MCP server for Atlassian Confluence integration with Claude Code, enabling search, read, create, update pages, manage labels, and list spaces via natural language.

Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.

This MCP server enables reading and analyzing various file formats, including PDF, DOCX, XLSX, and CSV, by extracting metadata, searching for keywords, and reading structured content. It also provides capabilities to create new documents and convert files between supported formats.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

MCP server enabling LLMs to query a local Calibre Content Server for ebook metadata, chapters, and content in HTML or Markdown.

Enables NPC agents to read, write, search, and manage a shared corporate document store, and to turn Mission Scripts into structured report outlines and scaffolds aligned to strategic intent.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

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.

MCP server for bidirectional Markdown-to-Confluence sync, enabling download and publish of Confluence pages as Markdown with images, frontmatter tracking, and dry-run safety.

Enables searching and retrieving Confluence pages, listing children, and updating pages as drafts, integrating Confluence documentation as context in Claude Code.

Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.

An MCP server that gives AI agents access to configured databases (PostgreSQL, MySQL, Redshift, SQL Server) with SSH/AWS SSM tunnels, pluggable secret providers, and strict per-instance isolation.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

MCP server providing advanced operations for Confluence Data Center, including page moving, storage file management, and space template syncing.

Enables document format conversion between Word, Markdown, PDF, HTML, and plain text, supporting batch operations and format validation via the AI MCP protocol.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

MCP server for managing product documentation as markdown files. Supports creating, reading, updating, deleting, and searching docs with optional semantic search.

A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.

Provides AI agents with multi-format document indexing, hybrid dense and sparse search with reranking, and relational SQL querying over extracted tables.

Enables clients to inspect local PDFs by searching text, rendering pages, and cropping selected regions at high resolution directly from the source document. It runs locally over stdio without requiring models, embeddings, GPUs, or API keys, and does not modify source PDFs or send network requests.

Converts documents between Markdown, PDF, DOCX, and HTML locally with AI-friendly Markdown output and secure file access.