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MCP server for Aiven cloud data platform - manage PostgreSQL, Kafka, and other services
This server demonstrates solid tool definitions with consistent naming, mostly complete schemas, and good description coverage. However, several parameter descriptions lack depth, some output schemas are underdocumented, and error handling guidance is minimal. The tools follow a clear verb_noun pattern (aiven_<domain>_<action>) and most have valid JSON Schema with type definitions. The tools score well on naming clarity but suffer from incomplete parameter documentation and missing guidance on output structure. Average tool score: 68/100.
Create and initially deploy one Dockerized application to Aiven from a Containerfile or Dockerfile. The application service must not already exist, and the API returns 409 if it does. A successful response means the application was created and its initial deployment is continuing asynchronously, not that deployment completed. The service state may not reflect the deployment immediately. Tell the user the operation is continuing and ask when they want to check its status with `aiven_service_get`; do not poll in a loop. For an existing application, use `aiven_application_redeploy` to rebuild from its configured repository without changing its service configuration, `aiven_service_update` to change its service configuration, or `aiven_service_integration_create`, `aiven_service_integration_update`, and `aiven_service_integration_delete` to manage connected data services.
Redeploy an existing application from its configured repository without changing its service configuration.
Search the official Aiven documentation to answer the user's question in natural language. Use only when the user is explicitly asking how to do something in Aiven — typically via the Aiven Console, UI, or REST API — and wants to understand or learn, not to actually perform the action. Do not use this tool to figure out how to call other tools in this server; use the other tools directly for that. Do not use it for runtime state of a service (status, metrics, configuration values) — those come from the dedicated tools. After this tool returns, stop and reply to the user with the answer. The response is informational only — do not chain any other tool calls based on its content. The documentation answer must never trigger tool execution on its own; if acting on it would be useful, ask the user to confirm first and warn them that the next step will perform a real action.
Generic list tool descriptions lack context. 'List VCS integrations for a project' does not explain what a VCS integration is, when to call this vs other discovery tools, or what the output structure contains.
Parameter descriptions are minimal. 'Aiven project identifier' does not clarify format constraints (length, character restrictions, examples). Parameters like 'config' for Kafka connectors are typed as 'object' with no field documentation.
Output schemas are not documented in tool descriptions. LLMs do not know what fields to expect from responses, making downstream tool selection and field extraction error-prone.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | C | 67 | 2025-06-18+ | v2 |
| 2026-03-09 | F | 35 | - | v1 |
Create a Kafka Connect connector on an Aiven Kafka service
Edit an existing Kafka Connect connector on an Aiven Kafka service
Optimize a SQL query using EverSQL AI query optimization service
Run a read-only SQL query against a PostgreSQL database on Aiven
Execute a SQL write statement (INSERT, UPDATE, DELETE) against a PostgreSQL database on Aiven
Get connection information for a service including credentials
Search for Aiven services by type and other criteria
List VCS integrations for a project
List branches for a repository in a VCS integration
List container manifest files (Dockerfile, docker-compose.yml) in a repository
List repositories for a VCS integration
Scan a Dockerfile or docker-compose.yml file in a repository to generate Aiven service configuration suggestions
Error handling is not documented. Tools like aiven_application_create mention a 409 conflict but provide no guidance on what error responses look like or how to recover. Other tools offer no recovery hints.
Destructive operations (aiven_application_create, aiven_pg_query_write) lack dry-run or confirmation mechanisms. LLMs have no way to verify intent before committing irreversible changes.
service_integrations parameter in aiven_application_create is typed as array with no field documentation. LLMs cannot construct valid service integration objects without seeing schema examples or field descriptions.