context-engineering
66 servers · 4,777★ total
Community edition of RepoPrompt: a native macOS context engineering app for AI coding agents, with an MCP CLI.
Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations
Local-first AI coding memory for AI agents. Records issues, attempts, fixes and decisions, then warns your agent before it repeats an approach that already failed. Native MCP server for Claude Code, Cursor, Antigravity and Codex. 100% local, no cloud, no telemetry. MIT.
Portable semantic memory for AI agents: core engine, TypeScript SDK, framework adapters, MCP server, CLI, and host plugins.
Save thousands of lines of code by building universal, domain-agnostic Multi-Agent Systems (MAS) through high-level semantic orchestration. This repository provides a production-ready blueprint for the Agentic Era, allowing you to replace rigid, hard-coded workflows with a dynamic transparent Context Engine that provides 100% transparency.
Mine your Claude Code and Codex logs into a local you.md agent profile.
Stop re-explaining your data to your AI every session. The individual-analyst context layer, delivered over MCP (Claude Code / Cursor / Codex).
Open-source control plane for Codex projects: Git-backed context, visible agent progress, scoped MCP access, resumable work, and safe handoffs.
Fast local-first Rust CLI for codebase metrics, AST-compressed LLM context bundles, and built-in MCP server.
Compass is a context engine that builds a knowledge graph of your organization's metadata, capturing entities, relationships, and lineage across systems and time, making it discoverable and queryable for both humans and AI agents.
Codebase Context gives AI agents understanding of your codebase through semantic code search, team conventions, patterns, and memory, so they use fewer tokens, spend less time, and produce better, more familiar output.
Git-native context engineering CLI and MCP server for AI coding agents. Keep specs, ADRs, rules, plans, and project knowledge in Git.
AI agent skills for building, operating and troubleshooting Apache Kafka applications. Topic audit, consumer lag, schema review, security, connectors and DLQ
Persistent, encrypted memory for AI agents: one Rust binary, one file, no cloud. 122 canonical MCP tools, hybrid recall, bi-temporal history, AES-256-GCM. Local-first, air-gap ready, MIT.
Master AI prompting for business innovation. O'Reilly Live Learning course by Tim Warner covering ChatGPT, Claude, Copilot, and enterprise prompt engineering with MCP implementation.
Keep Claude Code context clean. Open-source toolkit: drift detection, re-read dedup, integrity scoring, AST-aware reads, 15 MCP tools. 62.6% measured savings, reproducible.
Detects what your AI doesn't know about your project and fixes it. Post-training gap detection, runtime context injection via MCP.
Live context engine for AI agents: resolve verified workspace state before the context window opens. Pairs with Perseus Vault for persistent encrypted memory. Local-first, MIT. pip install perseus-ctx
Reliability gateway for AI tool output: schema-stable, secret-safe, pagination-complete JSON for MCP and CLI agents.
The #1 Obsidian MCP for AI memory — freshness-aware, cited, local-first and read-only by default. Dataview, Bases, PDFs, every agent.
Unified MCP context intelligence platform — pip-installable CLI that absorbed 6 foundational repos. Context engineering for AI agents.
🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph stores. Your AI assistant's long-term memory starts here.
The agent harness you steer — structured context, automatic staleness gates, and block-by-block review, all bound to your code. Local-first, MCP-native, open source.
Code intelligence for agents: find the code that matters and keep your context window and tokens lean.
Secure AI Memory with Dynamic Project Detection, Automatic Session Briefing, Personal+Team Session Summary Prompts, Triple Search, Knowledge Graphs, GitHub Integration (Issues, PRs, Actions, Kanban, Milestones), Team Collaboration, Hush, Adaptive Analytics, Markdown I/O, Audit+Token Logging, OAuth 2.1 & HTTP/SSE/stdio. 70+ Tools in 1 Code Mode.
Data Wiki turns data into portable knowledge bundles following Open Knowledge Format (OKF) and serves them to AI agents over the Model Context Protocol (MCP).
A persistent memory MCP server for Claude Code - Recursive Language Model integration for Claude Code inspired by MIT CSAIL paper
Local task-state ledger for AI coding agents. Preserve decisions, source conclusions, evidence, and checkpoints across Codex, Claude Code, Cursor, and other MCP clients.
Optimized, auditable execution for Codex and Claude Code: bounded repository context, verified patches, and reproducible paired benchmarks.
MCP-native infrastructure for persistent AI agent memory with encrypted storage, semantic retrieval and cross-agent continuity.
Persistent memory for AI coding agents via MCP — a bitemporal knowledge graph of your codebase, served to Claude Code, Cursor, Gemini CLI, and any MCP client. Tree-sitter + Gemini Flash → Neo4j (via Graphiti). 12 MCP tools, hierarchical clusters, two-regime confidence decay.
Agent memory that needs no API key, no LLM, and no embedding provider. One command on Bun and it is serving MCP over stdio against a local SQLite store. Drop-in for the MCP reference memory server. Every memory keeps its source, who may read it, and the evidence that contradicts it.
Local-first memory runtime for AI agents. One command to connect Claude Code, Codex, ChatGPT, MCP workflows, and local agents.
Context Engineering is a MCP server that gives AI agents perfect understanding of your codebase. Eliminates context loss, reduces token usage, and generates comprehensive feature plans in minutes. Compatible with Cursor, Claude Code, and VS Code.
TypeScript MCP gateway that connects AI agents to backend APIs via the Model Context Protocol — pluggable auth, V8 sandbox execution, circuit breaker, and audit logging.
Deterministic, self-hosted long-term memory for AI agents: store facts instead of transcripts, recall only what matters.
Local-first repo maps for coding agents—ranked files, test routes, risks, CLI/MCP/GitHub Action, and public GitHub URLs.
Local JSON memory store for context engineering with GitHub Copilot and MCP clients. Includes CLI, MCP server, and custom VS Code agent.
MCP proxy: zero-code GCF adoption. Wraps any MCP server, converts JSON to GCF mid-flight. 53-71% fewer tokens. Works with any structured data.
The continuity layer for everything you do with AI. A self-hosted, open source server any tool plugs into over MCP or REST: hybrid vector + lexical recall, an auto-built knowledge graph, sleep-style consolidation, procedural and persona tiers, OAuth 2.0, multi-tenant. SQLite or Postgres. MIT.
AILmanac — the always-current, community almanac for getting the most out of Claude and every AI. For all levels.
🧠 Kahuna is a context engineering platform. It's persistent memory for AI coding copilots. Teach it once, surface context automatically. MCP server for Claude Code.
An AI tech lead in server form—this intelligent MCP agent validates your coding agent's strategy, analyzes impact, and catches critical issues before any code is written. Like having a senior engineer review every approach, ensuring thoughtful architecture and fewer regressions.
Persistent codebase knowledge layer for AI agents. Pre-builds architecture, dependency, coupling, and risk knowledge served via MCP. 27 languages, 13 tools.
Open-source context engineering protocol for AI agents: governed retrieval, bounded multi-agent handoffs, MCP, provenance, recoverable effects, and replay.
Reliable memory and context infrastructure for AI coding agents: source-backed facts, review-gated learning, MCP/SDK/UI, and replaceable Qdrant/Graphiti retrieval.
A fast, model-agnostic coding agent for your terminal — built in Rust with a rich TUI, MCP, lossless context, safe tools, and built-in verification.
CLI for Model Context Protocol (MCP) servers. Pipe, script and automate MCP tools from the Unix shell, and keep their tool schemas out of your LLM context.
Use less context in Claude, Codex, and Cursor. Local AI memory and verifiable work briefs for long-running tasks.
MCP server for agent memory over HexxlaDB—ring retrieval, embeddings + lexical search, seams, facets, YAML persistence policy, localhost HTTP transport.
Measure the context-window tax an MCP server charges your AI agent — the real token cost of its tool schemas + responses. Ground truth (Anthropic count_tokens) or keyless estimate. Cross-platform single-file CLI.
Modular MCP server for programmatic prompt engineering. Provides intelligent prompt assembly for PRD generation, codebase analysis, and bug analysis with support for 31 technology stacks.
Shared context substrate for AI agents. Retrieval that learns what's useful. Runs local or cloud.
Claude Code Skills — the FAF Way · curated, receipt-proven skills that take any project to 100% AI-readiness · open SKILL.md format (Claude, Codex, Copilot, Gemini, Cursor)
Open-source, local-first control plane for multi-model AI coding agents in VS Code and MCP: task DAGs, source intelligence, durable context and evidence-based review.
Memory engine for self-evolving AI agent ecosystems. Multi-tenant, multi-space isolation with Bayesian truth maintenance, emotional valence, automatic consolidation, and configurable per-agent personality.
Persistent identity and memory across AI tools - mcp-native, local-first, framework-agnostic, production-ready.
Offline repository and workspace maps, wikis, dependency graphs, and context artifacts with file:line provenance, zero runtime dependencies, and MCP.
Open-source agent middleware — shared memory, credential isolation, and schema learning for AI agents. What one agent learns, every agent knows.
The local-first brain for coding agents: project memory + workflow intelligence + lossless ~50% context savings. MCP server + LLM proxy, zero cloud.
Long-term memory MCP server for AI coding agents. SQLite + FTS5 + vector search, CodeGraph, error learning, compaction survival. Beats Mem0 on benchmarks. No cloud, no API key.
Persistent Project Context for Rust MCP clients — IANA-registered .faf format · Rust-native MCP server