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:1.5.4
docker run -p 3000:3000 nubaeon/empirica:1.5.4 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-1.5.4.tar.gz (46.6 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-1.5.4-py3-none-any.whl (50.3 kB view details)

Uploaded Python 3

File details

Details for the file empirica_mcp-1.5.4.tar.gz.

File metadata

  • Download URL: empirica_mcp-1.5.4.tar.gz
  • Upload date:
  • Size: 46.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for empirica_mcp-1.5.4.tar.gz
Algorithm Hash digest
SHA256 8cafd57cd0b0c740da91fe4aa942770cca3907e5d89cfbea4b3d064f77c665e7
MD5 8506c00dcbfbde7615811675fa7c1289
BLAKE2b-256 779d33e58656957507c7bf48db14b811cb780594a69ef0be323ee2127b25bda2

See more details on using hashes here.

File details

Details for the file empirica_mcp-1.5.4-py3-none-any.whl.

File metadata

  • Download URL: empirica_mcp-1.5.4-py3-none-any.whl
  • Upload date:
  • Size: 50.3 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-1.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 d4169c00c4a0f3c6e8e2855bf8ab46da5de66888178d9afedcfe2946b80517b6
MD5 cea03c75d0d068e7ef8e616b566273f4
BLAKE2b-256 8647d1041153f9d4482645f325bbb73ec445feb66a2077057fb25290cf28e92a

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