chitta-bridge 0.7.0

MCP server for multi-model AI discussions — cloud, agentic CLIs, local GPU models, soul memory

Chitta Bridge

MCP server for multi-model AI discussions — connect Claude Code to any AI backend: cloud providers, agentic CLIs, and local GPU models.

Quick Start

# 1. Install
uv pip install git+https://github.com/genomewalker/chitta-bridge.git

# 2. Register with Claude Code
chitta-bridge-install

# 3. Use in Claude Code
# The tools are now available - Claude will use them automatically

Features

• Multiple backends: OpenCode, Codex CLI, and local GPU models (Ollama/vLLM)
• Continuous sessions: Conversation history persists across messages
• Session warmup: background ping captures session ID — subsequent calls skip cold start
• Multiple models: OpenCode (GPT-5.x, Claude, Gemini) + Codex (o3, o4-mini, gpt-4.1)
• Agent support: plan, build, explore, general agents (OpenCode)
• Agentic execution: Full-auto mode with sandboxed file operations (Codex)
• Variant control: Set reasoning effort (minimal to max)
• File/image attachment: Share code files and images for context
• Session continuity: Conversations continue across tool calls
• Discussion rooms: async multi-agent roundtables — any mix of backends respond in parallel, see the full thread, synthesize into one answer

Installation

With uv (recommended)

uv pip install git+https://github.com/genomewalker/chitta-bridge.git

With pip

pip install git+https://github.com/genomewalker/chitta-bridge.git

From source

git clone https://github.com/genomewalker/chitta-bridge.git
cd chitta-bridge
pip install -e .

Register with Claude Code

# Install (registers MCP server)
chitta-bridge-install

# Verify
claude mcp list

# Uninstall
chitta-bridge-uninstall

OpenCode Backend

Tool	Description
opencode_start	Start a new session (auto-warms up, captures session ID)
opencode_discuss	Send a message
opencode_plan	Start planning discussion
opencode_brainstorm	Open-ended brainstorming
opencode_review	Review code
opencode_ping	Check if model is reachable
opencode_models	List available models
opencode_agents	List available agents
opencode_model	Change session model
opencode_agent	Change session agent
opencode_variant	Change reasoning effort
opencode_config	Show current configuration
opencode_configure	Set defaults (persisted)
opencode_history	Show conversation history
opencode_sessions	List all sessions
opencode_switch	Switch to another session
opencode_end	End current session
opencode_health	Server health check

Discussion Rooms

Async multi-agent roundtable — any mix of backends (OpenCode, Codex, local GPU models, Claude) post in parallel each round, each seeing the full thread before responding.

# Create a room with 3 participants (including a local GPU model)
room_create(
    room_id="my-room",
    topic="What's the best way to design a cache invalidation strategy?",
    participants='[
        {"name":"Codex-GPT54","backend":"codex","session_id":"existing-codex-session"},
        {"name":"Gemini","backend":"opencode","session_id":"existing-gemini-session"},
        {"name":"Llama","backend":"local","model":"llama3.3:70b","base_url":"http://gpunode01:11434/v1"}
    ]'
)

# Run 2 rounds (all participants respond in parallel each round)
room_run(room_id="my-room", rounds=2)

# Add a participant mid-discussion
room_add_participant(room_id="my-room", participant='{"name":"Claude","backend":"claude"}')

# Read the full transcript
room_read(room_id="my-room")

Tool	Description
room_create	Create a discussion room with named participants
room_add_participant	Add a participant to an existing room
room_run	Run N rounds — all participants respond in parallel
room_read	Read the full transcript
room_synthesize	Distill the transcript — consensus, disagreements, best answer, open questions

Synthesis

After running a room, distill the full discussion into a single answer. Any backend can act as synthesizer — Claude (default), local GPU model, OpenCode, or Codex.

room_synthesize(room_id="my-room")

# Use a local model as synthesizer
room_synthesize(
    room_id="my-room",
    synthesizer='{"name":"Qwen3","backend":"local","model":"qwen3:30b-a3b","base_url":"http://gpunode01:11434/v1"}'
)

Local Models (GPU Nodes)

Chat with local LLMs (Ollama / vLLM) running on GPU nodes — via Slurm auto-discovery or direct hostname.

# 1. Start Ollama on a Slurm GPU node (writes URL to /tmp/ollama-server-<model>.url)
slurm-serve-ollama.sh llama3.3:70b

# 2. Discover available nodes and models
local_discover()

# 3. Start a session (auto-discovers endpoint if omitted)
local_start(session_id="llm1", model="llama3.3:70b")

# 4. Chat
local_discuss(message="Explain cache invalidation strategies")

# Or specify node explicitly
local_start(session_id="llm2", model="qwen3:30b-a3b", endpoint="http://gpunode01:11434/v1")

Discovery order

1. /tmp/ollama-server-*.url cache files (written by slurm-serve-ollama.sh)
2. Your running Slurm GPU jobs (squeue --me)
3. CHITTA_BRIDGE_GPU_NODES=node1,node2 environment variable
4. localhost:11434 fallback

Tool	Description
local_discover	Find GPU nodes with Ollama/vLLM running
local_start	Start a session (auto-discovers endpoint)
local_discuss	Chat with the local model
local_models	List models available at an endpoint
local_sessions	List active local sessions
local_switch	Switch active session
local_end	End a session
local_history	Show conversation history
local_health	Health check

Web Search

Search the web and fetch pages directly from Claude Code — no API key needed (DuckDuckGo).

# Search
web_search(query="ancient metagenomics DNA damage authentication")

# Fetch a page
web_fetch(url="https://example.com/article", max_chars=12000)

Tool	Description
web_search	Search via DuckDuckGo — returns titles, URLs, snippets
web_fetch	Fetch a web page as plain text (HTML stripped)

Soul Memory (chittad)

Bidirectional memory bridge to the cc-soul daemon. Room discussions automatically pull relevant memories as context, and syntheses are stored back as episodes.

# Check if soul is running
soul_status()

# Recall memories
soul_recall(query="cache invalidation strategies", limit=5)

# Store a memory
soul_remember(content="Room discussion concluded X is better than Y", kind="episode")

# Smart context (memories + code symbols + graph)
soul_context(task="refactor authentication middleware")

Tool	Description
soul_recall	Search memories by query
soul_remember	Store a new memory
soul_context	Smart context assembly (memories + symbols + graph)
soul_status	Check if chittad is available

Discussion rooms automatically:

• Inject soul context at creation — participants see relevant memories
• Store synthesis back — room conclusions become soul episodes

Codex Backend

Tool	Description
codex_start	Start a new Codex session
codex_discuss	Send a message to Codex
codex_run	Run a one-off task (stateless)
codex_review	Run code review on repository
codex_model	Change session model
codex_config	Show Codex configuration
codex_configure	Set Codex defaults (persisted)
codex_history	Show conversation history
codex_sessions	List all Codex sessions
codex_switch	Switch to another session
codex_end	End current session
codex_health	Codex health check

Available Models

OpenCode

Provider	Models
openai	gpt-5.2-codex, gpt-5.1-codex-max, gpt-5.1-codex-mini
github-copilot	claude-opus-4.5, claude-sonnet-4.5, gpt-5, gemini-2.5-pro
opencode	gpt-5-nano (free), glm-4.7-free, grok-code

Run opencode models to see all available models.

Codex

Model	Description
o3	Default, high capability
o4-mini	Faster, lower cost
gpt-4.1	Alternative option

Configuration

Environment variables

# OpenCode
export OPENCODE_MODEL="openai/gpt-5.2-codex"
export OPENCODE_AGENT="plan"
export OPENCODE_VARIANT="medium"

# Codex
export CODEX_MODEL="o3"
export CODEX_SANDBOX="workspace-write"

Config file

~/.chitta-bridge/config.json:

{
  "model": "openai/gpt-5.2-codex",
  "agent": "plan",
  "variant": "medium",
  "codex_model": "o3",
  "codex_sandbox": "workspace-write"
}

OpenCode Variants (reasoning effort)

minimal -> low -> medium -> high -> xhigh -> max

Higher variants use more reasoning tokens for complex tasks.

Codex Sandbox Modes

Mode	Description
read-only	Can only read files
workspace-write	Can write to workspace (default)
danger-full-access	Full filesystem access (use with caution)

The full_auto option (default: true) enables low-friction execution with workspace-write sandbox.

Requirements

• Python 3.10+
• OpenCode CLI for opencode_* tools
• Codex CLI for codex_* tools
• Ollama or vLLM on a GPU node for local_* tools
• Claude Code

License

MIT