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 into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Inspect callable tools, capabilities, and parameters exposed to AI agents by 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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