asset-health-mcp
Provides asset anomaly scoring from Databricks, helping decide whether to dispatch a field technician.
Integrates with Salesforce Data Cloud and creates guarded Asset Health WorkOrders for field-service dispatch.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@asset-health-mcpValidate the latest meter reading for asset 4432 and score its anomaly."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
asset-health-mcp
An AI agent that decides whether to dispatch a field technician โ and refuses to act on data it can't trust.
Agentforce agent grounded on Salesforce Data Cloud, calling a custom MCP server for data-quality validation (Great Expectations) and anomaly scoring (Databricks), with a guarded Apex write-back that creates the WorkOrder.
๐ฅ 2-minute demo video โ watch the agent validate, score, create a work order, then refuse a corrupted batch.
Why this exists
Most agent demos let the LLM act on whatever data it retrieves. In field service, acting on a corrupted meter reading means dispatching a technician for nothing โ or worse, missing a failing asset. This project puts a data-trust gate in front of every agent decision:
readings โโโถ Ingestion API โโโถ Data Cloud (zero-copy grounding)
โ
โผ
Agentforce agent
โ 1. check_reading_quality MCP / Great Expectations
โ 2. score_asset_anomaly MCP / Databricks
โ 3. create work order Apex (guarded write-back)
โ
โผ
Salesforce WorkOrderRelated MCP server: qc-validator-mcp
Design decisions
Two curated MCP tools, not a data dump. The agent gets judgment (trust + severity); raw history reaches it separately through Data Cloud zero-copy grounding. Stays far inside Agentforce's tool budget.
Guards live server-side. The Apex action refuses untrusted data and normal-severity requests even if the agent asks โ agent instructions are not a security boundary (OWASP LLM07).
Idempotent write-back. Agents retry; duplicate field dispatches cost real money. One open Asset Health WorkOrder per asset, enforced in Apex.
Runs with zero credentials. Deterministic Databricks mock + GX ephemeral context mean
pytestis green on a fresh clone with no external services.
Stack
Python 3.11 ยท FastMCP (mcp 1.x) ยท Great Expectations 1.18 ยท Databricks (Unity Catalog) ยท Salesforce Data Cloud (Ingestion API, DMO grounding) ยท Agentforce ยท Apex
Repository layout
src/asset_health_mcp/ FastMCP server: tools, GX validation, Databricks client
pipeline/ Ingestion API pipeline โ Meter Reading DMO (fallback path)
force-app/ Apex write-back action + tests
databricks/ PySpark scoring job โ Unity Catalog Delta table with
UniForm (Iceberg) โ zero-copy File Federation ready
snowflake/ readings warehouse DDL + least-privilege key-pair
integration user for Query Federation
datacloud/ ZERO_COPY.md โ federation-mode decisions and setup
docs/ AGENT_BUILD.md (Agentforce wiring), demo script
tests/ smoke suite, green with zero external servicesZero-copy design in one line: readings stay in Snowflake (Query Federation, JDBC pushdown to an isolated XS warehouse), scores stay in Databricks (File Federation via UniForm/Iceberg, zero external compute) โ mode chosen per table on cost, not by default. Details: datacloud/ZERO_COPY.md.
Run it
pip install -e ".[dev]" && pytest # zero-credential smoke suite
python -m asset_health_mcp.server # stdio, for Claude Desktop
MCP_TRANSPORT=streamable-http \
python -m asset_health_mcp.server # HTTP, for Agentforce registry
sf project deploy start # Apex action + testsFull build runbook: docs/SETUP.md (step by step, ordered around trial-licence constraints) ยท agent wiring: docs/AGENT_BUILD.md ยท what runs on which edition and what is documented rather than demonstrated: docs/ENVIRONMENTS.md.
Known limits
Demo-grade auth (PAT, not OAuth service principal), precomputed scores rather than real-time model serving, single-org. Listed deliberately โ the point of the project is the architecture, not production hardening.
Built by Yamyle โ Senior Salesforce Architect & Data/AI Engineer. 20+ Salesforce certifications ยท integration frameworks for utilities and financial services.
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