r/pallas

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Robert Helewka 0cea5ece3a feat: add /healthz and /metrics endpoints, replace print with logging

- Add /healthz endpoint returning LLM provider validation status
- Add /metrics endpoint serving Prometheus metrics via prometheus_client
- Replace all print() calls in health.py with proper logging module
- Remove _PREFIX variable in favor of structured logger context

2026-04-10 11:22:26 +00:00

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Mnemosyne Integration — Pallas Reference

This document summarises the Pallas-specific changes required for Mnemosyne knowledge integration. The full specification lives in daedalus/docs/mnemosyne_integration.md.

Overview

Pallas agents gain access to Mnemosyne's content-type-aware knowledge graph as a downstream MCP server. Agents can search documents, browse libraries, retrieve items, and traverse the concept graph — all via standard MCP tool calls.

Configuration Changes

fastagent.config.yaml

Add the Mnemosyne MCP server:

mcp:
  servers:
    # ... existing servers (argos, neo4j_cypher, kernos, rommie, gitea, grafana) ...
    mnemosyne:
      transport: http
      url: "http://puck.incus:22091/mcp"

Agent Definitions

Research Agent (port 23031)

The knowledge agent in the research chain gains Mnemosyne access:

@fast.agent(name="search", servers=["argos"])
@fast.agent(name="knowledge", servers=["neo4j_cypher", "mnemosyne"])
@fast.chain(name="research", sequence=["search", "knowledge"], default=True)

The knowledge agent's system instruction should guide tool selection:

Use mnemosyne.search_knowledge for document content retrieval — it handles chunking, vector search, re-ranking, and content-type-aware context. Use neo4j_cypher for graph topology queries, relationship exploration, and data not managed by Mnemosyne.

Infrastructure Agent (port 23032)

No changes — Infrastructure does not use Mnemosyne.

Orchestrator (port 23033)

@fast.agent(name="research_sub", servers=["argos", "neo4j_cypher", "mnemosyne"])
@fast.agent(name="infra_sub", servers=["kernos", "gitea", "rommie"])
@fast.orchestrator(name="orchestrator", agents=["research_sub", "infra_sub"],
                   plan_type="iterative", default=True)

Registry Update

Update agent descriptions to reflect Mnemosyne access:

{
  "server": {
    "name": "ca.helu.ouranos/pallas-research",
    "title": "Research Agent",
    "description": "Web search via Argos, knowledge graph via Neo4j, and content library search via Mnemosyne",
    "version": "1.1.0",
    "remotes": [
      { "type": "streamable-http", "url": "http://puck.incus:23031/mcp" }
    ]
  }
}

Available Mnemosyne MCP Tools

These tools become available to agents with mnemosyne in their servers list:

Tool	Purpose	When to Use
`search_knowledge`	Hybrid vector + full-text + graph search with re-ranking	Document content retrieval, question answering over stored knowledge
`search_by_category`	Search scoped to a library type (fiction, technical, etc.)	When the user specifies or implies a content domain
`list_libraries`	List all knowledge libraries	Discovering what knowledge domains exist
`list_collections`	List collections within a library	Browsing a specific knowledge domain
`get_item`	Retrieve item metadata + chunk previews + concept links	Deep dive on a specific document/item
`get_concepts`	Traverse concept graph	Exploring relationships between topics, people, places

Downstream MCP Servers (Updated)

Server	Host	URL	Used by
argos	miranda.incus	`http://miranda.incus:25534/mcp`	Research, Orchestrator
neo4j_cypher	circe.helu.ca	`http://circe.helu.ca:22034/mcp`	Research, Orchestrator
mnemosyne	puck.incus	`http://puck.incus:22091/mcp`	Research, Orchestrator
kernos	caliban.incus	`http://caliban.incus:22021/mcp`	Infrastructure, Orchestrator
gitea	miranda.incus	`http://miranda.incus:25535/mcp`	Infrastructure, Orchestrator
rommie	caliban.incus	`http://caliban.incus:22031/mcp`	Infrastructure, Orchestrator
grafana	miranda.incus	`http://miranda.incus:25533/mcp`	Infrastructure

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