semantic-model-mcp-server

semantic-model-mcp-server is a Python MCP server that connects to Microsoft Fabric and Power BI semantic models to browse workspaces/datasets, retrieve and validate TMSL, execute DAX queries, and create/update models via TMSL. It also includes a Best Practice Analyzer (BPA) that evaluates TMSL against a set of industry/Microsoft-recommended rules, plus tooling for detecting and using local Power BI Desktop instances for development/testing.

Evaluated Apr 04, 2026 (27d ago)
Homepage ↗ Repo ↗ Ai Ml mcp power-bi fabric semantic-model tmsl dax best-practice-analyzer python development-tools
⚙ Agent Friendliness
44
/ 100
Can an agent use this?
🔒 Security
57
/ 100
Is it safe for agents?
⚡ Reliability
28
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
55
Documentation
60
Error Messages
0
Auth Simplicity
55
Rate Limits
0

🔒 Security

TLS Enforcement
80
Auth Strength
60
Scope Granularity
40
Dep. Hygiene
55
Secret Handling
50

Uses msal/azure-identity and pyodbc/pythonnet/psutil/requests per dependency manifest, suggesting standard enterprise auth patterns, but provided content does not describe token/secret handling (e.g., logging redaction) or specific authorization model/scope granularity. No documented TLS requirements or certificate validation settings are included in the provided README/manifests.

⚡ Reliability

Uptime/SLA
0
Version Stability
35
Breaking Changes
45
Error Recovery
30
AF Security Reliability

Best When

You are already working with Microsoft Fabric/Power BI semantic models and want MCP-driven tooling plus a TMSL/BPA workflow, including optional local Power BI Desktop validation.

Avoid When

You cannot reliably provide Azure AD authentication/permissions or you need rigorous API contracts (OpenAPI/structured error codes) and operational guarantees (idempotency, pagination, retry guidance).

Use Cases

  • Chat with a semantic model from an MCP-capable client (e.g., VS Code Copilot) using your own LLM
  • Analyze Fabric/Power BI semantic models for best-practice violations and quality gates
  • Retrieve TMSL definitions for review, validation, and version control
  • Run DAX queries against models for exploration and debugging
  • Generate or update semantic models by applying TMSL
  • Run BPA on models during development prior to deployment
  • Detect local Power BI Desktop instances and run local BPA/DAX validation

Not For

  • Production-grade automated CI/CD without verification of operational safety (create/modify tooling suggests risk if misused)
  • Environments lacking access to Fabric/Power BI or where the required authentication/permissions cannot be obtained
  • Teams that require a strongly specified, vendor-neutral REST/SDK interface for integration
  • Use cases requiring guaranteed, documented rate-limit behavior and idempotent semantics

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: Microsoft authentication (Azure AD) for Fabric/Power BI access (implied by prerequisites and dependency on msal/azure-identity)
OAuth: No Scopes: No

README states 'Valid Microsoft authentication (Azure AD)' is required. Specific OAuth flow details, required scopes, and token handling are not documented in the provided README content.

Pricing

Free tier: No
Requires CC: No

No pricing information is provided in the supplied content; this appears to be a self-hosted/open-source Python tool.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Write operations (create/update semantic models) could have side effects if the agent mis-specifies TMSL; guardrails/validation are not documented in the provided README.
  • Local Power BI Desktop detection relies on running processes/ports; behavior may vary across machines and can be timing-sensitive.
  • No explicit guidance is provided for safe retries of DAX execution/model updates.

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Scores are editorial opinions as of 2026-04-04.

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