Skip to main content

MCP server for Empirica epistemic framework

Project description

Empirica MCP Server

MCP (Model Context Protocol) server for Empirica epistemic framework

PyPI Python License


Installation

pip install empirica-mcp

Note: The MCP server requires the full Empirica package for stateful operations:

pip install empirica  # Recommended - includes empirica-mcp

Verify Installation

empirica --version      # CLI
empirica-mcp --help     # MCP server

Quick Start

1. Standard Mode

empirica-mcp

Works as a standard MCP tool provider. No epistemic layer.

2. Epistemic Mode

export EMPIRICA_EPISTEMIC_MODE=true
empirica-mcp

Every tool call now includes epistemic self-awareness - the server maintains vector state and routes behavior based on confidence/uncertainty.

3. Personality Profiles

# Cautious (investigates early)
export EMPIRICA_PERSONALITY=cautious_researcher

# Pragmatic (action-oriented)
export EMPIRICA_PERSONALITY=pragmatic_implementer

# Balanced (default)
export EMPIRICA_PERSONALITY=balanced_architect

# Adaptive (learns over time)
export EMPIRICA_PERSONALITY=adaptive_learner

Claude Desktop Configuration

Standard Mode

{
  "mcpServers": {
    "empirica": {
      "command": "empirica-mcp"
    }
  }
}

Epistemic Mode

{
  "mcpServers": {
    "empirica-epistemic": {
      "command": "bash",
      "args": [
        "-c",
        "EMPIRICA_EPISTEMIC_MODE=true EMPIRICA_PERSONALITY=balanced_architect empirica-mcp"
      ]
    }
  }
}

After editing config, restart Claude Desktop completely.


Available Tools

The MCP server exposes 60+ Empirica CLI commands as MCP tools:

Session Management:

  • session_create - Create new session
  • session_list - List sessions
  • session_show - Show session details

CASCADE Workflow:

  • preflight_submit - Submit PREFLIGHT assessment
  • check_submit - Execute CHECK gate
  • postflight_submit - Submit POSTFLIGHT assessment

Goals & Findings:

  • goals_create - Create goals
  • goals_list - List goals
  • finding_log - Log findings
  • unknown_log - Log unknowns

And many more...


Epistemic Responses

Standard Response

{
  "ok": true,
  "session_id": "abc123",
  "message": "Session created"
}

Epistemic Response

{
  "ok": true,
  "session_id": "abc123",
  "message": "Session created",

  "epistemic_state": {
    "vectors": {
      "know": 0.60,
      "uncertainty": 0.40,
      "context": 0.70,
      "clarity": 0.85
    },
    "routing": {
      "mode": "confident_implementation",
      "confidence": 0.85,
      "reasoning": "Know=0.60 >= 0.6, Uncertainty=0.40 < 0.5"
    }
  }
}

Behavioral Modes

Mode Trigger Behavior
clarify clarity < 0.6 Ask questions before proceeding
load_context context < 0.5 Load project data first
investigate uncertainty > 0.6 Systematic research
confident_implementation know >= 0.7, uncertainty < 0.4 Direct action
cautious_implementation Moderate vectors Careful, incremental steps

Troubleshooting

"empirica CLI not found"

# Check if empirica is in PATH
which empirica

# If not, install full package
pip install empirica

"Module not found: empirica"

# Install full package (not just MCP server)
pip install empirica

Claude Desktop not connecting

  1. Verify JSON syntax (no trailing commas)
  2. Quit Claude Desktop completely
  3. Restart Claude Desktop
  4. Check logs for errors

Docker

docker pull nubaeon/empirica:1.4.0
docker run -p 3000:3000 nubaeon/empirica:1.4.0 empirica-mcp

Requirements

  • Python 3.11+
  • empirica >= 1.4.0
  • mcp >= 1.0.0

Documentation

License

MIT License - See Empirica repository for details.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

empirica_mcp-1.4.1.tar.gz (39.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

empirica_mcp-1.4.1-py3-none-any.whl (42.6 kB view details)

Uploaded Python 3

File details

Details for the file empirica_mcp-1.4.1.tar.gz.

File metadata

  • Download URL: empirica_mcp-1.4.1.tar.gz
  • Upload date:
  • Size: 39.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for empirica_mcp-1.4.1.tar.gz
Algorithm Hash digest
SHA256 d97571007d365a90e7ab69f6811c0ff02a8d486ba3da40e100e246274be9f098
MD5 0b2c3dd72ec5f343a20691c73e1d8e38
BLAKE2b-256 f6430b23aa1b8ac987352c0fbe6dbbb4e6d2dc37b17400b99b9f9f7fdc18fb68

See more details on using hashes here.

File details

Details for the file empirica_mcp-1.4.1-py3-none-any.whl.

File metadata

  • Download URL: empirica_mcp-1.4.1-py3-none-any.whl
  • Upload date:
  • Size: 42.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for empirica_mcp-1.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3e93b580308a5bea234a813f335a0c946ac16df63681fb366fd2004a9ca44f29
MD5 5b92d2f7901586eb7eba703dca0b6a42
BLAKE2b-256 18d327dc1f6ae747f12bb0866973418a60415bf47d8ad14dae200d510f7fd059

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page