MCP Server for connecting to the AgentBridge Nexus
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# AgentBridge Nexus MCP Server Python MCP server that exposes AgentBridge backend actions as tools for AI coding agents. ## Status The backend/MCP terminal MVP is implemented and live-tested. The package currently provides: - backend HTTP client - testable tool functions - MCP `FastMCP` entrypoint - core lifecycle, artifact, coordination, audit, memory, and validation tools ## Environment Set these before running the MCP server: ```bash export AGENTBRIDGE_API_URL="http://localhost:8000" export AGENTBRIDGE_AGENT_KEY="abk_your_agent_key" ``` `AGENTBRIDGE_AGENT_KEY` should be one of the keys printed by: ```bash cd services/api .venv/bin/python scripts/seed_dev.py --apply ``` ## Tools - `agentbridge_heartbeat` - `agentbridge_create_handoff` - `agentbridge_list_handoffs` - `agentbridge_claim_handoff` - `agentbridge_submit_artifact` - `agentbridge_get_artifact` - `agentbridge_get_artifact_content` - `agentbridge_request_review` - `agentbridge_create_approval` - `agentbridge_submit_review` - `agentbridge_complete_handoff` - `agentbridge_acquire_file_lock` - `agentbridge_release_file_lock` - `agentbridge_list_file_locks` - `agentbridge_list_file_conflicts` - `agentbridge_resolve_file_conflict` - `agentbridge_list_audit_logs` - `agentbridge_create_project_memory` - `agentbridge_list_project_memory` - `agentbridge_search_project_memory` - `agentbridge_update_project_memory` - `agentbridge_delete_project_memory` - `agentbridge_start_work_session` - `agentbridge_list_work_sessions` - `agentbridge_checkpoint_progress` - `agentbridge_resume_project` Resume workflow tools: - `agentbridge_start_work_session` starts tracking a feature/task in progress. - `agentbridge_checkpoint_progress` records where the agent is before stopping. - `agentbridge_resume_project` generates the continuation packet and prompt for another agent. ## Run From this directory: ```bash python -m agentbridge_mcp.server ``` When installed as a package: ```bash agentbridge-mcp ``` ## One-Comm…
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