AccInt

Name: AccInt
Author: maxbaluev

@maxbaluev

关于 AccInt

AccInt is a local Work Model and MCP server for persistent scored agent memory, retrieval, commitments, browser/runtime observations, and outcome-based learning across coding agents.

#memory #mcp #agent-memory #developer-tools #ai-agents #retrieval

基本信息

分类

其他

传输方式

stdio

发布者

maxbaluev

提交者

Max Baluev

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "accint": {
      "command": "acc",
      "args": [
        "mcp"
      ]
    }
  }
}

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 AccInt?

AccInt is a local work model for coding agents that integrates scored memory, recursive retrieval, commitments, runtime/browser observations, and outcome feedback in one substrate. It exposes an MCP interface so agents can retrieve prior work, record decisions, and close the loop when reality validates or rejects an action.

How to use AccInt?

—

Key features of AccInt

Scored memory for prioritizing agent experiences
Recursive retrieval of relevant prior work
Commitments to track intended actions
Runtime and browser observations
Outcome feedback to validate or reject actions
MCP interface for integration with coding agents

Use cases of AccInt

—

FAQ from AccInt

What does AccInt do?

AccInt is a local work model for coding agents that provides scored memory, recursive retrieval, commitments, runtime/browser observations, and outcome feedback via an MCP interface.