Skip to main content
Glama
dgsuyob

Persistent AI agent brain MCP server providing embedded coding standards, automatic stack detection, and project memory that survives across conversations, with tools for retrieving standards, detecting tech stacks, saving/retrieving project context, and validating code.

by dgsuyob

dev-brain-mcp

Your AI agent's persistent brain. Coding standards that never get forgotten, stack detection, and project memory that survives across conversations.

Inspired by ponytail, codebase-memory-mcp, and Graft.

The Problem

AI coding agents forget your rules in long conversations. Skills and instructions get truncated from the context window after many iterations. This MCP server solves that by:

  1. Embedding rules in tool descriptions — tool descriptions live in the system prompt and NEVER get truncated

  2. Detecting your stack automatically — no need to tell the agent "this is a React + RTK project" every time

  3. Persistent project memory — notes, architectural decisions, and conventions survive across conversations

Related MCP server: dev-kit-mcp-server

Install

git clone https://github.com/YOUR_USERNAME/dev-brain-mcp.git
cd dev-brain-mcp
npm install

Setup in Antigravity 2.0

Go to Settings → MCP Servers and add:

{
  "mcpServers": {
    "dev-brain": {
      "command": "node",
      "args": ["C:/Users/david/Documents/dev-brain-mcp/server.js"]
    }
  }
}

⚠️ Update the path to wherever you cloned this repo.

Per-Project Configuration

Create .agents/mcp.json in your project root:

{
  "mcpServers": {
    "dev-brain": {
      "command": "node",
      "args": ["C:/path/to/dev-brain-mcp/server.js"]
    }
  }
}

Other Agents (Claude Code, Cursor, etc.)

Add to your MCP config:

{
  "mcpServers": {
    "dev-brain": {
      "command": "node",
      "args": ["/path/to/dev-brain-mcp/server.js"]
    }
  }
}

Tools

Tool

Description

When to use

get_coding_standards

Returns ponytail rules + stack-specific rules

Before writing code

detect_stack

Detects language, framework, dependencies

Start of every session

get_project_context

Retrieves persistent notes, decisions, conventions

Start of every conversation

save_project_context

Saves context that survives across sessions

After learning something important

validate_code

Checks code against standards

After writing code

list_known_projects

Lists all previously analyzed projects

When switching projects

Why It Works

Skills (ponytail, RTK rules):
  → Instructions read into conversation context
  → Get TRUNCATED after ~30 iterations
  → Agent forgets them completely ❌

MCP Tool Descriptions:
  → Live in the system prompt alongside tool definitions
  → NEVER get truncated, no matter how long the conversation
  → Agent always sees them ✅

Persistent Memory (projects.json):
  → Stored on disk, survives across conversations
  → Agent retrieves context at start of each session
  → No re-exploration needed ✅

Adding Your Own Rules

Edit lib/rules.js:

  • Universal rules: Add to UNIVERSAL_RULES.principles

  • Stack-specific rules: Add a new key to CONDITIONAL_RULES

  • Validation checks: Add patterns to validateCode()

License

MIT

F
license - not found
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

View all related MCP servers

Related MCP Connectors

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dgsuyob/dev-brain-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server