A network of agentic research specialists coordinated by a principal investigator agent. V1: web-search researcher MCP server + CLI shim.
ddaf7e85c3
TraceLogger now tracks monotonic start times for starter actions (web_search, fetch_url, synthesis_start, start) and attaches a duration_ms field to the matching completer (web_search_complete, fetch_url_complete, synthesis_complete, synthesis_error). The terminal 'complete' step gets total_duration_sec instead. Pairings are tightly sequential in the agent code (each _execute_tool call runs start→end before returning), so a simple dict keyed by starter name suffices — no queueing needed. An unpaired completer leaves duration unset and does not crash. Durations flow into both the JSONL trace and the structlog operational log, so OpenSearch queries can filter / aggregate by step latency without cross-row joins. Verified end-to-end on a real shallow query: web_search 5,233 ms web_search 3,006 ms synthesis_complete 27,658 ms complete 47.547 s total Synthesis is by far the slowest step — visible at a glance for the first time. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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|---|---|---|
| cli | ||
| obs | ||
| orchestrator | ||
| researchers | ||
| scripts | ||
| tests | ||
| .dockerignore | ||
| .gitignore | ||
| CLAUDE.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| Makefile | ||
| pyproject.toml | ||
| README.md | ||
Marchwarden
A network of agentic research specialists coordinated by a principal investigator agent.
Marchwarden researchers are stationed at the frontier of knowledge — they watch, search, synthesize, and report back what they find. Each specialist is self-contained, fault-tolerant, and exposed via MCP. The PI agent orchestrates them to answer complex, multi-domain questions.
V1: Single web-search researcher + CLI shim for development.
V2+: Multiple specialists (arxiv, database, internal docs, etc.) + PI orchestrator.
Quick start
# Clone
git clone https://forgejo.labbity.unbiasedgeek.com/archeious/marchwarden.git
cd marchwarden
# Install (Makefile shortcut — creates .venv and installs deps)
make install
# or manually:
python3 -m venv .venv && source .venv/bin/activate && pip install -e ".[dev]"
# Ask a question
marchwarden ask "What are ideal crops for a garden in Utah?"
# Replay a research session
marchwarden replay <trace_id>
Docker test environment
A reproducible container is available for running the test suite and the CLI without depending on the host's Python install:
scripts/docker-test.sh build # build the image
scripts/docker-test.sh test # run pytest
scripts/docker-test.sh ask "question" # run `marchwarden ask` end-to-end
# (mounts ~/secrets ro and ~/.marchwarden rw)
scripts/docker-test.sh replay <id> # replay a trace from ~/.marchwarden/traces
scripts/docker-test.sh shell # interactive bash in the container
Documentation
- Architecture — system design, researcher contract, MCP flow
- Development Guide — setup, running tests, debugging
- Research Contract — the
research()tool specification - Contributing — branching, commits, PR workflow
Status
- V1 scope: Issue #1
- Branch:
main(development) - Tests:
pytest tests/
Stack
- Language: Python 3.10+
- Agent framework: Anthropic Claude Agent SDK
- MCP server: Model Context Protocol
- Web search: Tavily API
License
(TBD)