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#local-first

8 results found

S

Same Stateless Agent Memory Engine

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI. SAME (Stateless Agent Memory Engine) is persistent memory for AI coding agents. It indexes your markdown notes locally — Obsidian vaults, Logseq graphs, or plain folders — and surfaces relevant context automatically through a 6-gate relevance chain. ~80% of prompts are correctly skipped so your agent isn't drowning in context it doesn't need. 12 MCP tools (9 read, 3 write): semantic search across your knowledge base, filtered search by domain/tag, federated search across multiple vaults, session context with pinned notes and handoffs, save decisions, create handoffs for the next session. SQLite + Ollama embeddings on localhost. Falls back to keyword search without Ollama. No outbound network calls, no telemetry, no accounts. Your notes never leave your machine. Works with Claude Code (hooks + MCP), Cursor, Windsurf, and any MCP client via stdio transport.

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In Memoria

Persistent codebase intelligence that gives agents memory across sessions.

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Cobolt

This is a cross-platform desktop application that allows you to chat with locally hosted LLMs and enjoy features like MCP support

C

Conductor By Thealxlabs

Local-first AI agent that unifies 25+ plugins (Spotify, Gmail, GitHub, Notion, Telegram, Vercel, and more) into a single orchestration framework. AES-256-GCM encrypted credentials, zero telemetry, supports Claude, GPT-4o, Gemini, and Ollama.

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Code-Index-MCP (Local-first Code Indexer)

Code indexing MCP server to provide context to coding agents.

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Desktop Commander

Run & Manage Long Processes - install, scrap, encode video, compile Search & Read & Edit files - including diff editing for speed and precision

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Nowledge Mem

The graph augmented, smart and local-first Personal Context Manager, or Personal Agent Memory, just works. Nowledge Mem ingests your agent’s summarized memories through its MCP tools or prompts, enabling you to enhance your memory and knowledge using a GraphRAG approach. By leveraging LLMs, embedding models, BM25, graph algorithms, and a built-in knowledge graph, Nowledge Mem makes building, searching, and exploring your personal knowledge easier than ever.

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