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AccInt

@maxbaluev

Repository

About 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

Basic information

Category

Other

Transports

stdio

Publisher

maxbaluev

Submitted by

Max Baluev

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Where can I find the repository and website?

Repository: https://github.com/maxbaluev/accreted-intelligence ; Website: https://accint.xyz

Comments

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