google-meridian-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_doc_sourcesA | List all available Google Meridian documentation sources, user guides, API references, and GitHub repository links. |
| search_doc_topicsA | Search Google Meridian documentation by topic or keyword (e.g., 'adstock', 'priors', 'budget optimizer', 'NUTS', 'R-hat', 'DAG', 'causal'). |
| fetch_docsB | Fetch and parse Google Meridian documentation or code into clean Markdown. |
| get_control_point_guideB | Provides operational parameters, math formulas, and bounds for data science control points. |
| get_mmm_workflow_guideB | Provides decision trees and iteration rules for modeling phases and iteration loops. |
| calculate_bayesian_priorA | Solves probability equations to convert 95% CIs into Meridian LogNormal (mu, sigma) prior parameters. |
| audit_model_first_principlesC | Audits model spec for identifiability, knot density, prior variance, and Hill parameter bounds. |
| synthesize_meridian_codeC | Synthesizes clean, portable, cloud-agnostic Python code for Google Meridian. |
| generate_schema_templateC | Generates a synthetic benchmarking CSV schema template matching Meridian's input format. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Each tool has a clearly distinct purpose. Documentation tools (fetch, list, search) are separated by action, guides target different aspects (control points vs workflow), and remaining tools cover calculation, auditing, code synthesis, and schema generation without overlap.
All tool names follow a consistent verb_noun pattern in snake_case, e.g., fetch_docs, get_control_point_guide, calculate_bayesian_prior, list_doc_sources. The verbs are varied but predictable, and there is no mixing of conventions.
With 9 tools, the set is well-scoped for a domain-specific MCP server. It covers documentation, guides, prior calculation, auditing, code synthesis, and schema generation without being overloaded or too sparse.
The tool surface covers core documentation, guides, prior calculation, and auditing. Minor gaps exist: missing tools for directly running models or retrieving results, but these may be handled by synthesized code. Overall, it's fairly complete for the stated purpose.