Manas
Enables interaction with a local knowledge repository via MCP, providing tools for capturing, indexing, and searching Markdown notes with Git version control and optional semantic search.
README
Manas
Manas is a local-first, Git-backed knowledge system for syncing, indexing, and searching AI conversations and other personal knowledge sources. Your canonical knowledge lives in a repository you own; rebuildable indexes, embeddings, credentials, and runtime state remain local.
Quick start
bun install
bun run src/cli.ts brain init --repo <knowledge-repository>
bun run src/cli.ts capture "A thought worth keeping" --repo <knowledge-repository>
bun run src/cli.ts brain index --repo <knowledge-repository> --store <local-pglite-directory>
bun run src/cli.ts brain search --repo <knowledge-repository> --store <local-pglite-directory> --query "what did we decide?"
The brain commands create and maintain Markdown pages in a separate Git repository. Every mutation is revision- and commit-aware, deletion is recoverable, and indexing reads an immutable Git snapshot. Manas also imports local exports from supported AI tools and can synchronize local Markdown and text folders.
Local semantic search with Ollama
Run an OpenAI-compatible embedding endpoint locally, then index embeddings into the local PGLite store:
ollama pull nomic-embed-text
bun run src/cli.ts brain embed --store <local-pglite-directory> --embedding-endpoint http://127.0.0.1:11434/v1/embeddings --embedding-model nomic-embed-text --embedding-dimensions 768
Use the same endpoint, model, and dimensions for semantic retrieval. Vectors stay in local PGLite; Markdown in the knowledge repository is unchanged.
Commands
manas sync [--provider <name>] [--dry-run]
manas import chatgpt <zip-or-json>
manas import claude <zip-or-json>
manas brain init --repo <knowledge-repository>
manas brain index --repo <knowledge-repository> --store <local-pglite-directory>
manas brain search --repo <knowledge-repository> --store <local-pglite-directory> --query <query>
manas serve
Run commands during development with bun run src/cli.ts. The package also exposes a TypeScript API:
import { BrainRepository, openPgliteBrainStore, indexBrainRepository } from "manas";
Configuration and privacy
All product environment variables use the MANAS_ prefix. Set MANAS_STATE to choose local state storage and MANAS_BRAIN_REPOSITORY (or --repo) to choose the knowledge repository.
serve starts a local MCP server. For loopback HTTP MCP, set a non-secret local token with MANAS_MCP_TOKEN and use MANAS_MCP_SCOPES to restrict access. Do not put credentials or local state inside the repository.
Manas can optionally use ZeroEntropy for managed semantic retrieval. That sends bounded transcript chunks to the configured service. Local PGLite embeddings are the privacy-preserving path; health reports optional remote services as degraded when unavailable.
Development
bun run full-verification
The release gate validates capability parity, runbooks, a disposable pgvector/PostgreSQL contract, secret scanning, tests, typechecking, formatting, build output, and git diff --check.
License
MIT © 2026 Collin Johnson.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。