Robert Helewka
49da024877
Capture the five debugging chapters from the bearer-forwarding rollout
so the knowledge doesn't live only in chat history:
1. Per-request bearer across anyio.TaskGroup boundary (ContextVar
snapshot semantics, httpx auth-header caching on persistent
connections, forward_inbound_auth pydantic-drop workaround).
2. install() idempotency guard shadowing three newly-added
monkey-patches — each patch now owns its own sentinel.
3. FastMCP on_call_tool context shape: context.message.name, not
context.message.params.name. Extractor returning None silently
killed the _PUBLIC_TOOLS bypass and downstream dispatch "await
None(...)" produced the terse 'object NoneType can't be used in
await expression' string that blocked Harper<->Mnemosyne.
4. Rich-TUI corruption by DEBUG openai/sse_starlette/mcp via root
logger inheriting logger.level=debug + our stderr StreamHandler.
Fixed by PALLAS_LOG_STDERR gate and PALLAS_ROOT_LOG_LEVEL split.
5. Current state table of PALLAS_LOG_* knobs + jq tail recipe.
Also add pallas.log and pallas._fastagent_patch to the Module Reference
table.
Pallas — FastAgent MCP Bridge
Pallas is the generic runtime that turns fast-agent agent definitions into StreamableHTTP MCP servers.
It is completely deployment-agnostic: all environment-specific values (agent names, ports, hosts, model) live in the calling project's agents.yaml and fastagent.config.yaml.
Installation
pip install git+ssh://git@git.helu.ca:22022/r/pallas.git
Or as a project dependency in pyproject.toml:
dependencies = [
"pallas-mcp @ git+ssh://git@git.helu.ca:22022/r/pallas.git",
]
Usage
Pallas reads configuration from the working directory at runtime.
my-project/
├── agents/
│ ├── __init__.py
│ └── jarvis.py # FastAgent definitions
├── agents.yaml # Deployment topology
├── fastagent.config.yaml # FastAgent + model config
└── fastagent.secrets.yaml # API keys (gitignored)
Run from your project root:
pallas # start all agents + registry
pallas --agent jarvis # start a single agent
Or via python -m:
python -m pallas.server
agents.yaml format
name: my-project # used in log prefixes and registry names
version: "1.0.0"
host: my-host.example.com # hostname for registry URLs
namespace: com.example.my-project
registry_port: 8200
agents:
jarvis:
module: agents.jarvis # importable Python module path
port: 8201
title: Jarvis
description: "My assistant agent"
depends_on: [research] # optional: start these first
research:
module: agents.research
port: 8250
title: Research Agent
description: "Web search and knowledge graph"
fastagent.config.yaml extensions
Pallas reads two extra keys beyond the standard fast-agent config:
default_model: openai.my-custom-model-name
# Explicit capability declarations — avoids brittle name-regex heuristics
model_capabilities:
vision: false
context_window: 200000
max_output_tokens: 32000
Capabilities are published in the registry and used to register unknown models
with fast-agent's ModelDatabase.
Environment variable
| Variable | Default | Purpose |
|---|---|---|
PALLAS_AGENTS_CONFIG |
agents.yaml |
Override path to deployment config |
What Pallas provides
| Module | Purpose |
|---|---|
pallas.server |
CLI entry point and agent orchestration |
pallas.registry |
GET /.well-known/mcp/server.json registry server |
pallas.multimodal_server |
MultimodalAgentMCPServer — AgentMCPServer subclass with image support |
pallas.health |
LLM preflight validation + get_health MCP tool |