"App element selection for context" matching MCP servers:

Enables repository context packing, file/symbol ranking, task-relevant selection, and applying structured patches via MCP.

Enables app intelligence across Google Play and the Apple App Store, including details, reviews, and search via a unified API.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

An MCP server that provides live status updates for the Eco via Sirens game server, displaying meteor countdowns, player statistics, and world information directly within Claude Desktop. It also serves as a minimal reference implementation for building MCP Apps in Python without complex tooling.

Durable project-memory MCP: decisions, constraints, and pipelines across Claude sessions

Enables AI assistants to search and retrieve encrypted local screen history, including OCR text, recent activity, context around moments, daily rollups, and screen snapshots.

Enables LLMs to access a user's personal writing context—voice, style, opinions, expertise, projects, and communication patterns—via curated markdown files, helping the LLM match the user's voice when generating written content.

Enables MCP-compatible AI clients to interpret the init-app CLI, explore its supported blueprints, and translate natural-language project requirements into validated command arguments without executing the CLI.

A Model Context Protocol server that gives AI assistants persistent, scoped memory by saving and retrieving short notes (mementos) across sessions and projects, enabling dynamic learning and context injection without heavy dependencies.

Context Forge is a vendor-neutral continuity layer for AI tools. It stores project context in Markdown and JSON, retrieves task-scoped context, and leaves structured handoffs so another model can continue without being taught the project again.

Local-first memory for AI agents about the people in your life. MCP server + CLI on SQLite. Never phones home.

Provides local, explicitly scoped memory for coding agents via MCP, storing durable project knowledge in a per-repository SQLite database with tools to record, search, and retrieve context.

Enables multiple AI coding agents and humans to coordinate through a Git-native Markdown blackboard (.context/ + AGENTS.md), where they can inspect workspace overviews, claim and toggle ready tasks, record architecture decisions, synthesize shared prompts, and hand off work via atomic, lock-protected writes that prevent lost updates and formatting drift. It also serves a fully offline local web dashboard that live-syncs any blackboard change over WebSocket.

Enables LLM agents to compress handoffs into structured, auditable context capsules, preserving goals, constraints, decisions, and risks without external API calls.

An MCP server with LangGraph agent integration that enables AI agents to use custom tools and external APIs for dice rolling, web search, social content creation, and GitHub access via STDIO transport.

Enables local-first context retrieval and management from JSONL and Markdown sources through MCP, with a rebuildable full-text search index and support for stable reference pagination.

MCP server that integrates with chat tools to provide context from local projects, enabling reviewed and cited prompts.

Enables interaction with Hack The Box App services including machines, challenges, sherlocks, and more through the HTB API v4.