"Twitter MCP (Model Context Protocol) Server" matching MCP servers:

A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.

A stateful gateway server for AI applications that solves the memory limitations of Large Language Models by maintaining separate conversation contexts for each user.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

An MCP server that reads all your Claude Code project memory files and exposes them as tools. Lets any Claude instance — in any project, or via Claude.ai — query your full project history and preferences.

Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.

Provides persistent memory and a codebase knowledge graph for AI coding assistants, enabling shared context across multiple tools like Claude, Cursor, and ChatGPT, with significant token reduction.

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.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

Persistent 3D/2D spatial world model MCP server for AI agents. Entity tracking, object permanence, AABB collision simulation & view frustum projection via local SQLite.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.

Temporal knowledge graph for codebases that captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook.

An MCP server for saving, managing, and enhancing context with pre-processing strategies like clarification, analysis, and search optimization.

Context Portal (ConPort): A memory bank MCP server building a project-specific knowledge graph to supercharge AI assistants. Enables powerful Retrieval Augmented Generation (RAG) for context-aware development in your IDE.

Resume-as-an-Agent (RAAA) or Portfolio-as-an-Agent (PAAA) allows Agents to talk to your resume, find out if you are available for work, and more. Use the MCP to allow recruiters, managers, and anyone with an agent to "talk" to your resume.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

Provides local, evidence-aware research memory with human review, revision history, and an inspector, allowing assistants to preserve source reports, inferences, assumptions, and evidence across sessions.

Enables persistent multimodal context storage for LLM agents with thread-based scoping, metadata filtering, and hybrid search capabilities.

A CloudFlare Workers-based MCP server that provides semantic memory and journal capabilities with vector search. Enables users to store, search, and retrieve memories and journal entries using AI-powered semantic similarity without any local setup required.