Robert Helewka
679a809f66
The Mnemosyne Authorization: Bearer token was being dropped on outbound MCP
calls because fast-agent runs downstream transports inside a long-lived
anyio TaskGroup whose context is snapshotted at manager startup —
request_bearer_token.get() inside _prepare_headers_and_auth therefore
always resolved to None even when the request handler had just set it.
Fix:
* pallas/_fastagent_patch.py
- add _pending_bearers registry keyed by id(server_config) with a
threading.Lock; publish_bearer / revoke_bearer helpers.
- patched _prepare_headers_and_auth reads the registry first, falls
back to the ContextVar for non-persistent probe paths.
- emit INFO log on install() so the journal shows the patch ran;
verbose flow logs at DEBUG on pallas.forward.
* pallas/multimodal_server.py
- send_message resolves the agent's opted-in downstreams, publishes
the inbound bearer for each, and revokes them all in the finally.
- bearer/header diagnostics go to pallas.auth (DEBUG) instead of
/tmp/pallas-bearer.log which is invisible under systemd PrivateTmp.
* pallas/log.py
- honour PALLAS_LOG_LEVEL env var (default INFO) so operators can
flip the forward/auth diagnostics on without a code change.
* docs/pallas.md, docs/mnemosyne_integration.md
- document the registry-based forwarding and the task-group
ContextVar constraint that forced it.
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 |