hermes-agent/agent/transports/hermes_tools_mcp_server.py
Teknium f0a8e45cdc chore(mcp): drop stale input_schema comment on add_tool call
Review nit from verification: the comment claimed newer FastMCP accepts a
JSON schema kwarg — the installed SDK's add_tool has no such parameter; the
synthesized __signature__ is what drives schema generation on both paths.
2026-07-14 21:36:32 -07:00

284 lines
11 KiB
Python

"""Hermes-tools-as-MCP server for the codex_app_server runtime.
When the user runs `openai/*` turns through the codex app-server, codex
owns the loop and builds its own tool list. By default, that means
Hermes' richer tool surface — web search, browser automation,
delegate_task subagents, vision analysis, persistent memory, skills,
cross-session search, image generation, TTS — is unreachable.
This module exposes a curated subset of those Hermes tools to the
spawned codex subprocess via stdio MCP. Codex registers it as a normal
MCP server (per `~/.codex/config.toml [mcp_servers.hermes-tools]`) and
the user gets full Hermes capability inside a Codex turn.
Scope (what we expose):
- web_search, web_extract — Firecrawl, no codex equivalent
- browser_navigate / _click / _type / — Camofox/Browserbase automation
_snapshot / _scroll / _back / _press /
_get_images / _console / _vision
- vision_analyze — image inspection by vision model
- image_generate — image generation
- skill_view, skills_list — Hermes' skill library
- text_to_speech — TTS
- kanban_* (complete/block/comment/ — kanban worker + orchestrator
heartbeat/show/list/create/ handoff (stateless: read env var,
unblock/link) write ~/.hermes/kanban.db)
What we DO NOT expose:
- terminal / shell — codex's own shell tool
- read_file / write_file / patch — codex's apply_patch + shell
- search_files / process — codex's shell
- clarify — codex's own UX
- delegate_task / memory / — `_AGENT_LOOP_TOOLS` in Hermes
session_search / todo (model_tools.py). They require
the running AIAgent context to
dispatch (mid-loop state), so a
stateless MCP callback can't
drive them. See the inline
comment on EXPOSED_TOOLS below.
Run with: python -m agent.transports.hermes_tools_mcp_server
Spawned by: CodexAppServerSession.ensure_started() when the runtime is
active and config opts in.
"""
from __future__ import annotations
import inspect
import json
import logging
import os
import sys
from typing import Any, Optional
logger = logging.getLogger(__name__)
# JSON Schema type -> Python type mapping for signature generation
_JSON_TO_PY = {
"string": str,
"integer": int,
"number": float,
"boolean": bool,
"array": list,
"object": dict,
}
def _signature_from_schema(schema: dict | None) -> tuple[inspect.Signature, dict[str, type]]:
"""Build a Python function signature and annotations from a JSON schema.
Args:
schema: JSON Schema dict with "properties" and "required" keys.
Returns:
(signature, annotations_dict) where signature has KEYWORD_ONLY params
and annotations maps param names to Python types.
"""
props = (schema or {}).get("properties") or {}
required = set((schema or {}).get("required") or [])
params, annots = [], {}
for pname, pspec in props.items():
if pname.startswith("_"):
continue
py = _JSON_TO_PY.get((pspec or {}).get("type"), Any)
ann, default = (
(py, inspect.Parameter.empty)
if pname in required
else (Optional[py], None)
)
annots[pname] = ann
params.append(
inspect.Parameter(
pname, inspect.Parameter.KEYWORD_ONLY, annotation=ann, default=default
)
)
return inspect.Signature(params, return_annotation=str), annots
# Tools we expose. Each name MUST match a registered Hermes tool that
# `model_tools.handle_function_call()` can dispatch.
#
# What we deliberately DO NOT expose:
# - terminal / shell / read_file / write_file / patch / search_files /
# process — codex's built-ins cover these and approval routes through
# codex's own UI.
# - delegate_task / memory / session_search / todo — these are
# `_AGENT_LOOP_TOOLS` in Hermes (model_tools.py:493). They require
# the running AIAgent context to dispatch (mid-loop state), so a
# stateless MCP callback can't drive them. Hermes' default runtime
# keeps these working; the codex_app_server runtime cannot.
EXPOSED_TOOLS: tuple[str, ...] = (
"web_search",
"web_extract",
"browser_navigate",
"browser_click",
"browser_type",
"browser_press",
"browser_snapshot",
"browser_scroll",
"browser_back",
"browser_get_images",
"browser_console",
"browser_vision",
"vision_analyze",
"image_generate",
"skill_view",
"skills_list",
"text_to_speech",
# Kanban worker handoff tools — gated on HERMES_KANBAN_TASK env var
# (set by the kanban dispatcher when spawning a worker). Without these
# in the callback, a worker spawned with openai_runtime=codex_app_server
# could do the work but couldn't report completion back to the kernel,
# making it hang until timeout. Stateless dispatch — they just read
# the env var and write to ~/.hermes/kanban.db.
"kanban_complete",
"kanban_block",
"kanban_comment",
"kanban_heartbeat",
"kanban_show",
"kanban_list",
# NOTE: kanban_create / kanban_unblock / kanban_link are orchestrator-
# only — the kanban tool gates them on HERMES_KANBAN_TASK being unset.
# They're exposed here for orchestrator agents running on the codex
# runtime that need to dispatch new tasks.
"kanban_create",
"kanban_unblock",
"kanban_link",
)
def _build_server() -> Any:
"""Create the FastMCP server with Hermes tools attached. Lazy imports
so the module can be imported without the mcp package installed
(we degrade to a clear error only when actually run)."""
try:
from mcp.server.fastmcp import FastMCP
except ImportError as exc: # pragma: no cover - install hint
raise ImportError(
f"hermes-tools MCP server requires the 'mcp' package: {exc}"
) from exc
# Discover Hermes tools so dispatch works.
from model_tools import (
get_tool_definitions,
handle_function_call,
)
mcp = FastMCP(
"hermes-tools",
instructions=(
"Hermes Agent's tool surface, exposed for use inside a Codex "
"session. Use these for capabilities Codex's built-in toolset "
"doesn't cover: web search/extract, browser automation, "
"subagent delegation, vision, image generation, persistent "
"memory, skills, and cross-session search."
),
)
# Pull authoritative Hermes tool schemas for the ones we expose, so
# MCP clients see the same parameter docs Hermes gives the model.
all_defs = {
td["function"]["name"]: td["function"]
for td in (get_tool_definitions(quiet_mode=True) or [])
if isinstance(td, dict) and td.get("type") == "function"
}
exposed_count = 0
for name in EXPOSED_TOOLS:
spec = all_defs.get(name)
if spec is None:
logger.debug(
"skipping %s — not registered in this Hermes process", name
)
continue
description = spec.get("description") or f"Hermes {name} tool"
params_schema = spec.get("parameters") or {"type": "object", "properties": {}}
# FastMCP wants a Python callable. Build a closure that takes the
# arguments dict, dispatches via handle_function_call, and returns
# the result string. We use add_tool() for full control over the
# input schema (FastMCP's @tool() decorator inspects type hints,
# which we can't get from a JSON schema at runtime).
def _make_handler(tool_name: str, schema: dict | None):
sig, annots = _signature_from_schema(schema)
def _dispatch(**kwargs: Any) -> str:
try:
# Filter out None values before dispatch so unset optionals
# aren't forwarded to the handler.
args = {k: v for k, v in kwargs.items() if v is not None}
return handle_function_call(tool_name, args or {})
except Exception as exc:
logger.exception("tool %s raised", tool_name)
return json.dumps({"error": str(exc), "tool": tool_name})
_dispatch.__name__ = tool_name
_dispatch.__doc__ = description
_dispatch.__signature__ = sig
_dispatch.__annotations__ = {**annots, "return": str}
return _dispatch
try:
mcp.add_tool(
_make_handler(name, params_schema),
name=name,
description=description,
)
except TypeError:
# Older mcp SDK signature — fall back to decorator-style. The
# synthesized __signature__ on the handler still drives schema
# generation there.
handler = _make_handler(name, params_schema)
handler = mcp.tool(name=name, description=description)(handler)
exposed_count += 1
logger.info(
"hermes-tools MCP server registered %d/%d tools",
exposed_count,
len(EXPOSED_TOOLS),
)
return mcp
def main(argv: Optional[list[str]] = None) -> int:
"""Entry point for `python -m agent.transports.hermes_tools_mcp_server`."""
argv = argv or sys.argv[1:]
verbose = "--verbose" in argv or "-v" in argv
log_level = logging.INFO if verbose else logging.WARNING
logging.basicConfig(
level=log_level,
stream=sys.stderr, # MCP uses stdio for protocol — logs MUST go to stderr
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
)
# Quiet mode: keep Hermes' own banners off stdout (which is the MCP wire).
os.environ.setdefault("HERMES_QUIET", "1")
os.environ.setdefault("HERMES_REDACT_SECRETS", "true")
try:
server = _build_server()
except ImportError as exc:
sys.stderr.write(f"hermes-tools MCP server cannot start: {exc}\n")
return 2
# FastMCP runs with stdio transport by default when launched as a
# subprocess.
try:
server.run()
except KeyboardInterrupt:
return 0
except Exception as exc:
logger.exception("hermes-tools MCP server crashed")
sys.stderr.write(f"hermes-tools MCP server error: {exc}\n")
return 1
return 0
if __name__ == "__main__":
sys.exit(main())