Behavioral Identity Models

v1.0.0Knowledge & Memorystable

Serves portable behavioral identity models via MCP. Extracts how a person thinks, communicates, and makes decisions from text, then provides always-on identity context, semantic fact retrieval, keyword search, and provenance tracing through 4 tools a

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What is Behavioral Identity Models?

Behavioral Identity Models is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to serves portable behavioral identity models via mcp. extracts how a person thinks, communicates, and makes decisions from text, then provides always-on identity context, semantic fact retrieval, keywor...

Serves portable behavioral identity models via MCP. Extracts how a person thinks, communicates, and makes decisions from text, then provides always-on identity context, semantic fact retrieval, keyword search, and provenance tracing through 4 tools a

This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Serves portable behavioral identity models via MCP. Extracts

Use Cases

Extract behavioral patterns from text
Persistent identity context for agents
Semantic fact retrieval and provenance tracking
agulaya24

Maintainer

LicenseApache 2.0
Languagetypescript
Versionv1.0.0
UpdatedApr 24, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx baselayer

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Behavioral Identity Models

BaseLayer builds a portable behavioral identity model from your conversation history — chat exports from ChatGPT, Claude, or journals — and serves it over MCP so any AI assistant can access a persistent, semantically searchable understanding of how you think, communicate, and make decisions. The pipeline extracts facts and episodes using the Anthropic API, embeds them into a local ChromaDB vector store, then exposes four primary tools: get_brief for a unified narrative, recall_memories for semantic search, search_facts for keyword lookup, and trace_claim for provenance tracing. This gives agents always-on identity context without re-uploading your data each session.

Prerequisites

  • Python 3.10 or higher installed
  • An Anthropic API key from console.anthropic.com (required for extraction and composition steps)
  • A conversation export file (ChatGPT export zip, Claude export, or markdown notes)
  • An MCP-compatible client (Claude Desktop, Claude Code, or Cursor)
  • git installed to clone from GitHub (not yet on PyPI)
1

Install BaseLayer from GitHub

BaseLayer is not on PyPI yet. Install directly from the GitHub repository using pip's git support.

pip install git+https://github.com/agulaya24/BaseLayer.git
2

Set your Anthropic API key

Export your Anthropic API key as an environment variable. BaseLayer uses Claude models during the extraction, embedding, and composition phases of the pipeline.

export ANTHROPIC_API_KEY=sk-ant-your-key-here
3

Run the full pipeline on your conversation export

Point the pipeline at your exported conversation file. For a ChatGPT export, pass the zip file directly. Processing ~1,000 conversations takes about 30 minutes and costs roughly $0.50–$2.00 in API credits.

baselayer run chatgpt-export.zip
4

Register the MCP server with your client

Once the identity model is built, register the BaseLayer MCP server so your AI client can query it. For Claude Code or Claude Desktop, use the mcp add command.

claude mcp add --transport stdio base-layer -- baselayer-mcp
5

Verify the tools are available

Restart your MCP client. The tools get_brief, recall_memories, search_facts, and trace_claim should now appear. Ask your assistant for a brief to confirm the identity model loaded correctly.

Behavioral Identity Models Examples

Client configuration

Claude Desktop configuration block for BaseLayer MCP server running over stdio with the Anthropic API key.

{
  "mcpServers": {
    "base-layer": {
      "command": "baselayer-mcp",
      "args": [],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-your-key-here"
      }
    }
  }
}

Prompts to try

Example prompts that use the identity model tools to give agents persistent context about the user.

- "Give me a brief overview of how I think and communicate based on my identity model"
- "What do I tend to prioritize when making technical decisions?"
- "Search my memories for anything related to how I handled the product launch last year"
- "Find facts about my communication style preferences"
- "Trace where the claim about my leadership approach comes from in my original conversations"

Troubleshooting Behavioral Identity Models

baselayer command not found after installation

The pip install may have placed the binary in a location not on your PATH. Try running `python -m baselayer` instead, or check ~/.local/bin and add it to your PATH.

Pipeline fails with Anthropic API errors during extraction

Verify ANTHROPIC_API_KEY is exported correctly and the key has sufficient credits. For large exports, the extraction step can consume several dollars in API calls — run `baselayer estimate` before `baselayer extract` to preview the cost.

recall_memories returns empty results

The ChromaDB vector store must be built before the MCP server can serve results. Ensure you ran the full pipeline (baselayer extract && baselayer embed) before starting baselayer-mcp. Re-run the pipeline if the database was deleted.

Frequently Asked Questions about Behavioral Identity Models

What is Behavioral Identity Models?

Behavioral Identity Models is a Model Context Protocol (MCP) server that serves portable behavioral identity models via mcp. extracts how a person thinks, communicates, and makes decisions from text, then provides always-on identity context, semantic fact retrieval, keyword search, and provenance tracing through 4 tools a It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Behavioral Identity Models?

Follow the installation instructions on the Behavioral Identity Models GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Behavioral Identity Models?

Behavioral Identity Models works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Behavioral Identity Models free to use?

Yes, Behavioral Identity Models is open source and available under the Apache 2.0 license. You can use it freely in both personal and commercial projects.

Browse More Knowledge & Memory MCP Servers

Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "baselayer": { "command": "npx", "args": ["-y", "baselayer"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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