hermes_bridge — connect the belt to another agent framework

botte-secrète already runs a standard MCP server (skills.llm_mcp.server, stdio JSON-RPC). If the target framework speaks MCP, that's the whole integration — no code in this module runs:

python -m skills.hermes_bridge.cli config --cwd /path/to/botte-secrete
# → paste the printed {"mcpServers": {...}} block into the framework's MCP config

This module exists for frameworks — [[hermes-second-brain]] among them — that instead expect a flat list of OpenAI-function-calling tool specs + a dispatcher, a common shape for agents built before/without MCP support.

python -m skills.hermes_bridge.cli schemas          # focused tool specs, OpenAI-shaped
python -m skills.hermes_bridge.cli call botte_auto_route --prompt "rename x to y"

from skills.hermes_bridge import TOOL_SCHEMAS, dispatch

# register TOOL_SCHEMAS with the framework's tool-calling mechanism, then:
dispatch("botte_auto_route", {"prompt": "..."})   # → JSON string, same shape as the MCP tool

Focused tools

Deliberately a subset of the ~35-tool MCP surface — the ones that matter for a second-brain / routing integration:

Why this matters for a second-brain agent

Every task [[hermes-second-brain]] would otherwise send straight to its own model gets a chance to resolve locally or via the cheapest capable tier first — see [[bench]] for the measured (not asserted) savings from that. botte_find_skills also gives Hermes 0-token access to the local skill catalog instead of re-deriving capabilities from scratch each session.

Related: [[llm_mcp]] (the native MCP server this bridges from), [[auto_router]], [[bench]] (the proof), docs/integrations/hermes.md (the full integration write-up).