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297,942 tools. Last updated 2026-07-14 09:59

"clickhouse" matching MCP tools:

  • Deploys a MULTI-CONTAINER app — a repo that ships a docker-compose.yml / compose.yaml (app + its own db/redis/worker containers) — onto ONE VM via podman-compose, and exposes ONE service at https://<name>-<id>.redu.cloud. Use this instead of deploy_app when the repo is a compose stack rather than a single Dockerfile. SAME prereqs + source modes as deploy_app: run check_deploy_prerequisites (network_id + keypair_name), then GIT (`repo`, +git_token for private) or UPLOAD (prepare_upload → source_token). PORT: pass the HOST port the exposed service publishes (the LEFT side of its `ports:` mapping) — redu probes + proxies that exact port; pass `service` to name which service it is (plan_deploy detects both). DB: 'compose' (default) uses the stack's own db service (self-contained); 'single_vm'/'managed' provision a Postgres/MySQL and APPEND its conn env (DATABASE_URL/PG*/MYSQL_*) to the project .env — your compose must REFERENCE those vars to use it (we never rewrite your compose file). Build+provision can take 4-40 min (it pulls/builds every service — heavy ClickHouse/Kafka stacks are slow); poll get_deployment until status='ready', and on failure read build_log (it captures podman-compose logs). TIPS: (1) prefer the project's PREBUILT published images — swap any `build:` block for the published `image:` tag (building from source on the VM is less reliable). (2) redu injects APP_URL/PUBLIC_URL (= the app's public URL) into the env — map the app's own URL/cookie-domain var (SERVER_URL/NEXTAUTH_URL/…) to ${PUBLIC_URL}. (3) multi-surface apps (dashboard + API on separate ports) → pass `expose:[{port,service},…]`, each gets its own URL. (4) if the stack needs a ONE-TIME DB migrate/prepare before it serves (Rails `rails db:prepare`, Django `migrate`, Prisma `migrate deploy` — e.g. Lago), pass `migrate_command` (+ `migrate_service`); without it the stack deploys to 'ready' but 502s on real use because the schema is missing. ALWAYS run plan_deploy first and confirm the plan + cost with the user.
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  • Aggregated trace statistics for one agent over the last N days — total runs, success rate, avg duration, error breakdown, top tools used, runs-per-day histogram. Use this when you want a bird's-eye view of an agent's health before diving into individual traces with `agents.traces_list` / `agents.trace_get`. Scoped to the target agent (exact match, no substring bleed). `days` is capped at 30 — matches the ClickHouse request_traces TTL.
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  • Deletes a managed ClickHouse database and its underlying VM. Pass the numeric id from list_clickhouse_databases. This cannot be undone.
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  • Aggregated trace statistics for one agent over the last N days — total runs, success rate, avg duration, error breakdown, top tools used, runs-per-day histogram. Use this when you want a bird's-eye view of an agent's health before diving into individual traces with `agents.traces_list` / `agents.trace_get`. Scoped to the target agent (exact match, no substring bleed). `days` is capped at 30 — matches the ClickHouse request_traces TTL.
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  • Provisions a managed MySQL (or MariaDB) database on a dedicated VM on your private network — the relational-database resource (use this instead of create_database when the app needs MySQL/MariaDB, e.g. WordPress, NextCloud, Matomo, many PHP/LAMP apps). Requires a recent plan_managed_datastore. For app deployments, prefer deploy_app database:'managed' with db_engine mysql/mariadb so plan_deploy includes and wires the DB automatically. It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP (port 3306), not a public address. Get the ids from plan_managed_datastore/list_flavors/list_private_networks/list_keypairs. Provisioning takes ~5 min; poll list_relational_databases until status='ready', then the connection details (private_ip, port 3306, db_name, db_user) are populated. MySQL is created with mysql_native_password auth so older clients/apps connect cleanly. (ClickHouse is a separate resource — use create_clickhouse / list_clickhouse_databases.)
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  • Lists your managed ClickHouse databases (OLAP / analytics — its own resource, not a relational DB). Once a row's status is 'ready' it carries the private-network connection details (private_ip, ClickHouse HTTP port 8123, db_name, db_user).
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  • AI data intelligence platform that brings your data warehouse, dashboards, monitoring, and accumulated business knowledge into any MCP client. Connects to BigQuery, Snowflake, PostgreSQL, MySQL, ClickHouse, Redshift, Databricks, SQL Server, and Azure Synapse.

  • Browse, query, and administer your managed WaveHouse + ClickHouse projects (schema, pipes, policy).

  • Provisions a managed ClickHouse database (OLAP / columnar analytics engine, Apache-2.0) on a dedicated VM on your private network — its OWN resource, NOT a relational database. Requires a recent plan_managed_datastore. Use it for analytics / observability workloads that need a column store (PostHog, Langfuse, event analytics, time-series). It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP on the ClickHouse HTTP port 8123 (CLICKHOUSE_HOST/PORT/USER/PASSWORD/DB env, http://host:8123). Get the ids from plan_managed_datastore/list_flavors (use m1.small+ — ClickHouse needs >=2GB RAM), list_private_networks, list_keypairs. Provisioning takes ~5 min; poll list_clickhouse_databases until status='ready'.
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  • Read-only. Fetches EVERY resource on your redu.cloud account (VMs, volumes, private networks, managed databases: Postgres/MySQL/MariaDB/ClickHouse/Redis/Qdrant, load balancers, and DNS access points) and renders ONE Mermaid diagram of the whole account, grouped into per-private-network subgraphs with repetition collapsed into count nodes (e.g. "App VM x12"). Returns report_markdown to save as redu_architecture_diagram.md at the repo root, PLUS a redu_md_section that enriches the repo's redu.md with the current account topology, so the NEXT deploy is account-aware: it integrates with services that already exist and picks models/versions/sizes that fit the stack (better decisions, not just avoiding duplicate networks/databases). Nothing is created or changed.
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