"Developing a FHIR-Based Digital Health Application with EHR, PHR, and Phenotyping Frameworks" matching MCP servers:

A local-first, open-source MCP server that analyzes jobs, matches your CV, tailors documents, and tracks applications — all on your machine with no data uploaded.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

A Model Context Protocol server that scrapes blog posts from V2.ai Insights, extracts content, and provides AI-powered summaries using OpenAI's GPT-4.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

A Python-based MCP server that allows users to create, read, and manage digital sticky notes with Claude integration for AI-powered note summarization.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.

Integrates Vale prose linting into AI coding assistants, enabling users to check text files for style and grammar issues using Vale's powerful linting engine. Provides automated style feedback with smart configuration discovery and rich formatted results.

Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.