Shawn Core MCP

Shawn Core MCP is a local-first JSON-RPC MCP server for practical specialist routing, continuity, and evidence-based handoffs.

The public orchestrator is named Orchestrator. It retains a concise map of every specialist for ordinary tasks and escalates only when deeper proof is needed. That keeps routing helpful without turning every small request into a multi-agent ceremony.

Every public specialist has the same 8/10 contract baseline: intake, evidence, handoff, and public boundary. This measures public operational completeness, not a claim that every domain has identical technical depth.

Included core tools

• orchestrator_route: return the first specialist and validation plan.

• token_master_audit: inventory token-relevant local configuration facts.

• changelog_intake: start a lightweight changelog subprocess plan with an Atlas Cartographer handoff, a local Git snapshot, and an @github handoff.

• changelog_finalize: render a receipt-backed changelog entry at task end.

• atlas_continuity_record: write a compact, payload-free Cartographer card beneath an operator-selected local continuity root.

• personal_git_snapshot: read status and latest commit from an allowlisted local Git repository.

• personal_git_commit: make an explicit local commit only within roots allowlisted by SHAWN_CORE_GIT_ROOTS.

The Changelog specialist is configured for gpt-5.6-luna, a 64,000-token compaction target, and a 100,000-token hard ceiling. Those are an execution contract for the host that runs the subprocess, not an attempt to claim that an MCP can raise a provider's actual context window.

Related MCP server: ITHZ MCP

Run locally

python -m unittest discover -s tests -v
$env:SHAWN_CORE_GIT_ROOTS = "<local-repository-root>"
python -m shawn_core_mcp.server

Send newline-delimited JSON-RPC requests over standard input. The server is local only. It does not open a port, read credentials, change model settings, or publish to GitHub.

Public boundary

This repository intentionally excludes personal configuration, model and dataset paths, cloud credentials, client material, generated outputs, and private specialist implementations. GitHub publication is performed by the operator, not by the MCP.