"Improving React Native Development Experience" matching MCP servers:

Provides a cross-session experience knowledge base for AI agents, enabling retrieval of past problem-solution experiences via MCP tools. It helps agents reuse solutions without retraining, with zero-LLM runtime retrieval.

Enables AI agents to persistently recall, apply, and reinforce solutions to previously solved problems across different models and tools, so mistakes are not repeated.

A lightweight, dependency-free MCP server that answers cited queries over a Tero corpus index.json via stdio JSON-RPC 2.0, with honest refusal semantics and no silent empty results.

An MCP-native document research agent that provides search, summarization, and citation tools for iterative multi-step research, ending in validated structured JSON reports.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

A personal knowledge hub MCP server that allows LLMs to query Akib Dabgar's skills, experience, projects, and education using Dynamic Context Retrieval.

A local RAG MCP server for PDF development experience, enabling document ingestion, semantic search, and Q\&A with source citations using TF-IDF and cosine similarity.

heroicons-mcp is a Model Context Protocol (MCP) server that exposes Heroicons. It allows LLMs and agentic applications to search, list, and generate usage examples of icons in React applications.

A lightweight server that provides curated, high-quality prompts for common development tasks like UI/UX design, project setup, and debugging to enhance AI-powered development workflows.

Provides AI assistants with a persistent knowledge graph and experience memory, featuring context-aware routing, progressive disclosure, decay-based forgetting, and automatic promotion of important knowledge. It offers 22 MCP tools for storing, recalling, connecting, and querying knowledge, experiences, preferences, and ideas.

Provides a 'think' tool that allows Claude and other LLMs to add dedicated thinking steps during complex tool use scenarios, creating space for structured reasoning and improving problem-solving capabilities.

An MCP server that provides a self-improving knowledge graph with per-triple provenance and deterministic reasoning, enabling auditable, reproducible, and contradiction-aware answers for AI agents.

Enables AI development tools to perform semantic search and document relationship analysis on vectorized content stored in Qdrant databases.

Agent-native developer Q&A service providing MCP tooling and A2A runtime endpoints for deep research and citations.

Provides a find_solution tool that retrieves verified, compressed coding solutions from a curated library and injects them into AI coding agents like Claude Code and Cursor via MCP, improving problem-solving success rates by up to 50%.

Provides 78 tools for AGI experiments based on universal physics principles like entropy and criticality. It enables advanced long-term memory management, diversity-focused information retrieval, and meta-cognitive monitoring for self-improving AI systems.

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

Self-improving documentation engine that ingests Slack and GitHub PRs to detect knowledge gaps and improve documentation automatically.

Provides semantic search and listing over a unified personal knowledge graph aggregating LinkedIn, GitHub, course completions, and more, enabling MCP clients to answer questions about skills and experience with evidence-backed results.

A self-hosted MCP server that retrieves git-backed engineering experience records (issues, fixes) to inform LLM coding agents, preventing repeated mistakes with a relevance floor.