"A tool or method for searching within PDF files" matching MCP servers:

Upload, edit, compress, protect, redact, and compare PDFs with KDAN PDF in Claude and ChatGPT.

Create, merge, split and fill PDF files on your machine from Claude, ChatGPT, Cursor or any MCP client, with no upload.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

Enables agents to read, search, and render PDFs confined to a single root folder, with hidden-text warnings and options to merge, split, and create PDFs from Markdown. Read-only by default, with writing tools offered only when explicitly enabled.

A comprehensive MCP server with 37 tools for PDF operations including reading, searching, creating, merging, splitting, watermarking, form filling, and more, built on open-source libraries.

Local Markdown-to-PDF MCP server with four tools to list themes, render a document, validate an existing PDF, and create a document from a template. Requires Python, Pango/GLib, and fonts; its 0–100 report is heuristic, not print or accessibility certification.

Enables AI agents to permanently remove personally identifiable information from PDF documents, returning redacted files with the sensitive text deleted rather than merely covered. Supports scanned documents, multiple languages, entity types, and optional human review.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Read selected local folders from ChatGPT on macOS, with per-folder read-only or read-write access and hash-checked, recoverable edits. Requires local installation and a private ChatGPT app. The Glama container is a synthetic evaluation demo; it does not connect to files on your Mac.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables AI coding agents to inspect digital or scanned PDF forms and worksheets, map detected answer slots through a virtual Excel/Set-of-Marks view, and inject baseline-snapped text, multi-line answers, or option marks into clean output PDFs. Supports visual verification of completed pages.

PDF Merge AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.

PDF Tools AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables MCP clients to audit local PDFs for accessibility issues, batch-audit folders, explain findings, compare reports, and render self-contained HTML, JSON, or Markdown reports without uploading documents or calling models.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

Lets a human review what an AI agent is about to post to a chat tool (Slack first) before it is sent. Renders the draft, destination and warnings (@here/@channel, unresolved mentions, format issues) in a neutral local HTML preview; never sends anything.

A local document processing toolkit for AI agents that extracts text, converts PDFs to Markdown, merges files, extracts tables, and summarizes documents without external API dependencies.

Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

Empowers AI agents to securely read and extract information (text, metadata, page count) from PDF files within project contexts using a flexible MCP tool.

A local stdio MCP server that enables validated access to official ElevenLabs APIs with cost controls, local media storage, and audio export for Godot.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.