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Attestor

@bolnet

代码仓库

关于 Attestor

Audit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval (no LLM in the critical path), conversation ingest with speaker-locked dual-pass extraction, per-tenant Postgres row-level

#memory#agent#multi-agent#llm#rag#knowledge-graph#bi-temporal#postgres#pgvector#neo4j#rbac#provenance#audit

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

bolnet

提交者

Surendra Singh

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "attestor": {
      "command": "attestor",
      "args": [
        "mcp"
      ],
      "env": {
        "ATTESTOR_DISABLE_LOCAL_EMBED": "1"
      }
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Attestor?

Attestor is a memory store for agent teams that need a shared, tenant-isolated memory with bi-temporal replay, deterministic retrieval, and an auditable supersession chain. It runs as a Python library, a Starlette REST service, or an MCP server — the same API in all three.

How to use Attestor?

Install via pip install attestor, set up local Postgres and Neo4j using attestor setup local, pull the default embedder (ollama pull bge-m3), then verify with attestor doctor. Use the Python API (AgentMemory, AgentContext) or run as an MCP server.

Key features of Attestor

  • Bi-temporal memories with event and transaction time axes for point-in-time reconstruction.
  • Deterministic six-step retrieval pipeline with no LLM in the hot path.
  • Tenant isolation via Postgres Row-Level Security.
  • Conversation ingest with two-pass speaker-locked

评论

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