Search: context-engine
Search MCP servers and agent skills by name, description, category or topic — 39 results.
deanpeters/context-engineering-advisor
Diagnose context stuffing vs. engineering and guide memory and retrieval design
topoteretes/cognee
Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources
muratcankoylan/context-fundamentals
Understand what context is, why it matters, and the anatomy of context in agent systems
muratcankoylan/context-degradation
Recognize patterns of context failure: lost-in-middle, poisoning, distraction, and clash
muratcankoylan/context-compression
Design and evaluate compression strategies for long-running sessions
muratcankoylan/context-optimization
Apply compaction, masking, and caching strategies
muratcankoylan/multi-agent-patterns
Master orchestrator, peer-to-peer, and hierarchical multi-agent architectures
muratcankoylan/memory-systems
Design short-term, long-term, and graph-based memory architectures
muratcankoylan/tool-design
Build tools that agents can use effectively, including architectural reduction patterns
NeoLabHQ/write-concisely
Applies the famous *The Elements of Style* book principles to make documentation and writing clearer and more professional by eliminating wordiness and improving structure.
NeoLabHQ/code-review
Comprehensive PR code review using specialized agents: bug-hunter, security-auditor, code-quality-reviewer, contracts-reviewer, historical-context-reviewer, test-coverage-reviewer
NeoLabHQ/reflexion
Self-refinement loop that forces the LLM to reflect on previous output and correct itself.
NeoLabHQ/sdd
Spec-driven development workflow that transforms prompts into production-ready implementations through structured planning, architecture design, and LLM-as-a-Judge based quality gates.
NeoLabHQ/ddd
Domain-driven development skills that also include Clean Architecture, SOLID principles, and design patterns.
NeoLabHQ/sadd
Dispatches independent subagents for individual tasks with code review checkpoints between iterations for rapid, controlled development.
NeoLabHQ/kaizen
Applies continuous improvement methodology with multiple analytical approaches, based on Japanese Kaizen philosophy and Lean methodology.
NeoLabHQ/prompt-engineering
Widely used prompt engineering techniques and patterns, including Anthropic best practices and agent persuasion principles.
juyterman1000/entroly
Auditable context control plane and MCP server for AI coding agents. Compresses context 70–95% (BM25 + entropy + dep-graph knapsack), stabilizes prompt prefixes for provider cache discounts, routes easy tasks to cheaper models (RAVS Bayesian router), and verifies answers locally with WITNESS hallucination guard (0.844 AUROC, $0, ~3 ms). MemoryOS adds local budget-aware working/episodic/semantic me
omega-memory/omega-memory
Persistent memory for AI coding agents with semantic search, auto-capture, cross-session learning, and intelligent forgetting. 28 MCP tools, local-first.
sheawinkler/ContextLattice
Private-by-default memory and context layer for agents with Go/Rust runtime, staged retrieval across fused data backends, and long-horizon context continuity.
adelinamart/robrain
Self-hosted decision memory for AI coding agents. Passively captures architectural decisions with the alternatives you rejected (structured `rejected[]`), then warns the agent before it re-proposes a rejected approach. Postgres + pgvector; cross-tool across Claude Code, Cursor, Copilot, and Codex. Install: `npx robrain up && npx robrain install`.
PatrickSys/codebase-context
Local MCP server that shows AI agents which patterns your team actually uses, what files a change will affect, and when there is not enough context to trust an edit. 30+ languages, fully local.
Perseus-Computing-LLC/perseus-vault
Local-first, MCP-native persistent memory for AI agents — a single Rust binary with embedded SQLite, hybrid FTS5 + dense-vector search, and optional AES-256-GCM encryption. Fully offline, no cloud.
Perseus-Computing-LLC/perseus
Local-first live context engine and MCP server. Pre-resolves git, services, tests, and memory into a ready context briefing at session start (compile-before-context). MIT, PyPI: perseus-ctx.
apecloud/ApeRAG
Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering
oomkapwn/enquire-mcp
Long-term memory for AI agents (Claude Code/Desktop, Cursor, ChatGPT, Codex, OpenClaw) backed by a local Obsidian markdown vault. Hybrid retrieval (BM25 + ML embeddings + BGE reranker, RRF-fused), HNSW + int8 quantization, agentic RAG (HyDE + sub-question), GraphRAG-light (Louvain wikilink community detection), standalone Obsidian Bases, PDFs + Tesseract OCR. 46 tools, 19 MCP prompts, MIT, SLSA L2
ihorponom/agentpack
Repo-native task continuity for AI coding agents: a reviewed task-state ledger (decisions, dead ends, evidence, checkpoints) in `.agentpack/` that any next session or client resumes from.
STiFLeR7/memex
Developer context continuity system. Watches your git repos and builds a temporal knowledge graph of modules, symbols, decisions, and open problems via Graphiti + Neo4j, then serves it to any AI coding agent over MCP. Every edge carries a validity window and a confidence score that decays over time. 12 tools across read and write. Install via `npx -y stifler-memex-mcp`. MIT licensed.
renezander030/agentic-task-system
Turns your task manager into agent memory: hybrid (dense + sparse + keyword, RRF) retrieval over TickTick or an Obsidian vault via a six-method adapter contract. MCP server + CLI, no vector DB to build or maintain. `npm i -g @reneza/ats-cli`
billy12151/memory-arbiter-mcp
AI enhancement middleware: precise retrieval replaces full-memory loading (~80%+ token cut), rule-based conflict arbitration with explainable reasons, and one local SQLite shared across Claude Code/Codex/Cursor/ZCode. Local-first, zero cloud, MIT. `pip install memory-arbiter-mcp`
foldwork-dev/mcp-injector
Local MCP daemon that pre-indexes your codebase into a SQLite catalog and serves AST-compressed snapshots to Claude Code, Cursor, and VS Code on every query. Reduces token usage by 41-89% on real codebases (verified across Django, Tokio, Gin, and more). Single Go binary, zero config. Free for codebases under 100K lines.
nomadop/session-watcher
EOQ-based context economics for coding agents. Monitors LLM token cache with inventory theory, signals optimal session restart timing via live dashboard and terminal statusline. Zero context pollution — no metric ever enters the model's context.
nikolay-e/diffctx
Selects the minimum code context an LLM needs to understand a git diff: graph-based fragment selection under a token budget, deterministic, 30+ languages. Published on PyPI and in the MCP Registry.
japlete/md-vision-mcp
Read Markdown with inlined images and heading indexes for agentic RAG over local docs or allowed URLs.
rushikeshmore/CodeCortex
Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client.
Auctalis/nocturnusai
Deterministic reasoning engine for AI agent context compression. Extracts structured facts with logical inference, proof chains, and truth maintenance. REST API, Python/TypeScript SDKs, and MCP server integration.