"Improving React Native Development Experience" matching MCP servers:

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

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 Codex, Pi, and CLI clients to retrieve design knowledge and SOPs, orchestrate local Vivado/FPGA and LTspice workflows, enforce checks, and verify or recover traceable execution evidence.

Enables any MCP client (zcode, Claude Code, Cursor) to give its model bi-temporal long-term memory, auditable evidence-cited retrieval, LLM-assisted document extraction, and deterministic A* skill planning with precondition/effect verification. All four capabilities share one portable SQLite store and can be mounted independently on demand.

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 self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.

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

An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.

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.

Enables AI coding assistants to query and store a team's historical development experience through semantic search, so lessons and decisions persist across conversations.

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.

Persistent reasoning memory for AI coding agents over MCP: decisions, evidence, corrections and experience history.

Provides AI agents and teams with self-hosted adaptive memory, combining hybrid search and a self-improving neural memory graph to enable precise recall and serendipitous discovery across MCP-compatible clients.

Enables AI assistants and development tools to perform intelligent web searches with natural language queries using Linkup's search API.

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.

Enables AI agents to share a persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from sources like Obsidian vaults, code, and transcripts through MCP and REST APIs. Provides token-optimized, tiered retrieval with full-text and semantic search so every agent session builds on accumulated context.

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 Claude Code to retain cross-session memory of facts, decisions, and lessons with semantic search, while tracking user corrections as behavioral patterns and evolving self-improving frameworks over time. All processing runs locally through an MCP server and hooks, requiring no cloud service or API key.

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

Enables AI assistants to operate DIANA FEA under human supervision, automate solver workflows, parse results, and retrieve knowledge from local manuals and experience libraries.

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%.

Enables AI agents to share a persistent, self-improving memory by ingesting sources like Obsidian vaults, code, transcripts, and session captures, then serving them back through search, classification, synthesis, and token-optimized context briefings. It lets multiple agents read and write the same knowledge base, so each session builds on the last without copy-pasting context.

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.

Enables AI agents to share persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from Obsidian vaults, code, documents, transcripts, bookmarks, and sessions through MCP and REST interfaces with token-optimized search.

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