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StarTree MCP Server for Apache Pinot

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by startreedata

update-table-config

Modify table configurations in Apache Pinot by updating the table name and config JSON. Skip specified validation types to customize updates.

Instructions

Update table configuration

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableConfigJsonYes
tableNameYes
validationTypesToSkipNo

Implementation Reference

  • FastMCP tool handler for the 'update_table_config' tool. Defines input schema via type annotations (tableName: str, tableConfigJson: str, optional validationTypesToSkip: str) and delegates execution to PinotClient.update_table_config, returning JSON results or error.
    @mcp.tool
    def update_table_config(
        tableName: str,
        tableConfigJson: str,
        validationTypesToSkip: Optional[str] = None,
    ) -> str:
        """Update table configuration"""
        try:
            results = pinot_client.update_table_config(
                tableName,
                tableConfigJson,
                validationTypesToSkip,
            )
            return json.dumps(results, indent=2)
        except Exception as e:
            return f"Error: {str(e)}"
  • Core implementation of table config update logic. Performs authenticated HTTP PUT request to Pinot controller's /tables/{tableName} endpoint with tableConfigJson payload and optional validationTypesToSkip param.
    def update_table_config(
        self,
        tableName: str,
        tableConfigJson: str,
        validationTypesToSkip: str | None = None,
    ) -> dict[str, Any]:
        url = f"{self.config.controller_url}/{PinotEndpoints.TABLES}/{tableName}"
        params: dict[str, str] = {}
        if validationTypesToSkip:
            params["validationTypesToSkip"] = validationTypesToSkip
        headers = self._create_auth_headers()
        headers["Content-Type"] = "application/json"
        response = requests.put(
            url,
            headers=headers,
            params=params,
            data=tableConfigJson,
            timeout=(self.config.connection_timeout, self.config.request_timeout),
            verify=True,
        )
        response.raise_for_status()
        try:
            return response.json()
        except requests.exceptions.JSONDecodeError:
            return {
                "status": "success",
                "message": "Table config update request processed.",
                "response_body": response.text,
            }
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'update' implies a mutation but fails to describe permissions needed, whether changes are reversible, side effects, or response format. This is inadequate for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single phrase, 'Update table configuration', which is front-loaded and wastes no words. However, this conciseness comes at the cost of underspecification, but it earns full marks for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is completely inadequate. It lacks essential details on behavior, parameters, usage, and output, making it insufficient for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning all three parameters (tableConfigJson, tableName, validationTypesToSkip) are undocumented in the schema. The description adds no information about these parameters, their purposes, formats, or examples, failing to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Update table configuration' restates the tool name 'update-table-config' with minimal elaboration, making it tautological. It specifies the verb 'update' and resource 'table configuration' but lacks detail on what aspects of configuration are updated or how this differs from sibling tools like 'update-schema' or 'create-table-config'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as 'create-table-config' or 'update-schema'. The description offers no context, prerequisites, or exclusions, leaving the agent with no usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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