The grounded data layer for any LLM: governed SQL, metrics, lineage and catalog over your data.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Matih MCP.
askCallable MCP tool function
list_connectionsCallable MCP tool function
list_databasesCallable MCP tool function
list_schemasCallable MCP tool function
search_ontologyCallable MCP tool function
get_entityCallable MCP tool function
Connect AI clients (Claude Desktop, ChatGPT, Cursor, β¦) to the Matih data platform over the Model Context Protocol. Write SQL, profile tables, run analyses + charts, manage dashboards, and upload files β all through MCP tools, with OAuth/PKCE auth and PII-safe egress.
New here? See QUICKSTART.md for a step-by-step customer guide β create a token, connect Claude Desktop / Cursor, and copy-paste
curlsmoke tests β plus a troubleshooting table.
Add to your client's MCP config. The token is delivered via the environment β never as a CLI flag (which leaks into the OS process list):
The bridge turns the remote Matih HTTP MCP endpoint into a local stdio MCP server,
forwarding every tools/call, resources/read, and prompts/get to Matih.
Endpoint: replace
<slug>with your workspace slug β your Matih app lives athttps://<slug>.app.matih.ai(the bareapp.matih.aihost does not resolve). Get amat_agt_β¦token from Settings β Developer Tokens. See QUICKSTART.md for the full walkthrough.
The provider runs RFC 9728 β RFC 8414 discovery, PKCE S256, RFC 8707 resource-bound
tokens, caches, and refreshes; a 401 invalid_token triggers one re-auth.
Discovery is the primary API β await client.tools() returns the live tool
descriptors and client.callTool(name, args) reaches every advertised tool.
The typed facade (MatihTools) covers the 34 stable tools
(STABLE_TOOL_NAMES):
ask (natural-language β grounded answer + the SQL it ran),
run_sql, run_analysis, get_query_result, export_resultlist_connections, list_databases, list_schemas,
list_tables, describe_table, profile_tablesearch_ontology, get_entity,
get_relationships, get_semantic_model, get_glossary, explore_graphget_metric, run_metric, draft_metric
(write-class β proposes a DRAFT metric_def into the human-gated
DRAFT β REVIEW β APPROVED β SHIP pipeline), list_metric_drafts,
export_semantic_model (OSI), get_taxonomy, export_taxonomy (SKOS)create_chart, create_dashboard, get_dashboard,
publish_dashboardupload_file, upload_status, create_upload_url, finalize_uploadwhoami, get_scopeThe 1 Beta tool (BETA_TOOL_NAMES: get_hot_context) is deliberately
not hard-typed while its shape may evolve β call it via
client.callTool(name, args). The governed metrics & taxonomy group and
explore_graph were promoted from Beta to stable in July 2026 (PDR W3-1).
Plus catalog / lineage resources and the explain_metric prompt. Every
tool is bounded by the developer token's scope (connections + capabilities you
grant in Settings) and never exceeds your own permissions β get_scope shows
exactly what a token allows.
EGRESS_CONSENT_REQUIRED error with a link to accept it.fetch + node:crypto; zero runtime dependencies).License: Apache-2.0 Β· https://matih.ai
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