sovereign-exoself-mcp

sovereign-exoself-mcp

Local MCP server for a personal AI Council that routes tasks through manager, worker, critic, synthesizer, and archivist agents with fast/review/full paths, using SQLite memory and supporting mock, Ollama, and OpenRouter providers.

Category
Visit Server

README

sovereign-exoself-mcp

Local MCP server for personal AI Council. Routes tasks through manager, worker, critic, synthesizer, and archivist with fast/review/full paths. Uses SQLite memory with WAL and FTS5. Supports mock, Ollama, and OpenRouter providers.

Architecture

flowchart LR
  C[MCP stdio client] --> T[3 tools]
  T --> O[Council Router]
  O --> M[Manager<br/>granite3.3:2b]
  M -->|fast| W[Worker<br/>qwen2.5-coder:7b]
  M -->|review| W
  M -->|full| W
  W -->|review| CR[Critic<br/>qwen2.5-coder:7b]
  CR -->|reject| W
  CR -->|approve| S[Synthesizer<br/>granite3.3:2b]
  S -->|full| A[Archivist<br/>granite3.3:2b]
  S --> R[Result]
  A --> R

Model Configuration (Config B)

Role Model Rationale
Manager granite3.3:2b Fast routing decisions
Worker qwen2.5-coder:7b Quality code execution
Critic qwen2.5-coder:7b Reliable code review
Synthesizer granite3.3:2b Fast result merging
Archivist granite3.3:2b Fast memory extraction

Benchmark: 1504ms avg, 3428ms P95, 100% success rate, 0 timeouts.

Quick Start

Requirements: Ubuntu/Linux, Python 3.14, uv.

cd /home/hat/AionUI/sovereign-exoself-mcp
bash scripts/install.sh
bash scripts/smoke_test.sh --mock

--mock mode requires no API key and is useful for offline validation. For real inference, run the server directly with a provider (see below). scripts/generate_client_configs.py auto-generates host snippets (dist/) that enable a real provider: ollama by default, openrouter when OPENROUTER_API_KEY is present.

Ollama Mode

# Pull required models
ollama pull granite3.3:2b
ollama pull qwen2.5-coder:7b

# Run with Ollama
SOVEREIGN_PROVIDER_MODE=ollama \
uv run python -m sovereign_exoself_mcp

OpenRouter Mode

# Secrets are environment-only: store the key in the gitignored `.env` file
echo "OPENROUTER_API_KEY=sk-or-v1-..." >> .env

SOVEREIGN_PROVIDER_MODE=openrouter \
uv run python -m sovereign_exoself_mcp

Council Routes

Fast Path (Default)

Manager → Worker → Result. Used for simple questions, facts, quick analysis.

Review Path

Manager → Worker → Critic → Synthesizer → Result. Used for code changes, architecture decisions.

Full Council

Manager → Worker → Critic → Synthesizer → Archivist → Result. Used for complex tasks requiring memory.

API Tools

council_run

{
  "task": "Review and improve the configuration loader.",
  "mode": "auto",
  "budget": "low",
  "worker_profile": null,
  "needs_memory": null,
  "max_rounds": null,
  "route_override": null
}

Mode values: auto (manager decides), code, analysis, decision. As a shorthand, mode also accepts fast, review, or full to force a route directly. An explicit route_override (fast/review/full) always wins when provided.

Response includes: run_id, status, route, models, result, metrics, memory_updates, warnings

memory_manage

{
  "action": "search",
  "query": "design decisions"
}

Actions: search, store, list, delete, export, profile

system_status

Returns health, provider mode, model mapping, prompt versions, active runs, Ollama status.

Changing Models

# Environment variables
export SOVEREIGN_OLLAMA_WORKER_MODEL=qwen3:8b
export SOVEREIGN_OLLAMA_MANAGER_MODEL=gemma2:2b

# Or config file
cp config/council.example.yaml config/council.yaml
# Edit config/council.yaml

Worker Profiles

Profile Purpose
code_engineer Code implementation, debugging, refactoring
system_engineer Infrastructure, DevOps, system design
researcher Information gathering, analysis
technical_writer Documentation, prose
planner Task decomposition, project planning
general_operator Default fallback

Running Benchmark

# Mock benchmark
python benchmarks/benchmark.py --mode mock

# Live benchmark (requires Ollama with models)
OLLAMA_TEST_MODEL=qwen2.5-coder:7b python benchmarks/benchmark.py --mode ollama

System Status

# Via MCP tool
system_status({})

# Via CLI
uv run python -c "import asyncio; from sovereign_exoself_mcp.providers import probe_ollama; print(asyncio.run(probe_ollama('http://127.0.0.1:11434', 5)))"

Rollback

  1. Set SOVEREIGN_PROVIDER_MODE=mock
  2. Remove new environment variables
  3. Revert code changes

Adding Worker Profiles

  1. Create src/sovereign_exoself_mcp/prompts/profiles/<name>.txt
  2. Add to PROFILES list in prompts.py
  3. Use in requests: {"worker_profile": "<name>"}

Environment Variables

See .env.example for all available settings.

Documentation

Testing

# Run all tests
python -m pytest tests/ -v

# Run specific test suite
python -m pytest tests/unit/test_prompts.py -v
python -m pytest tests/unit/test_router.py -v
python -m pytest tests/unit/test_schemas.py -v

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured