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Netlify MCP Server

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by netlify

netlify-team-services-reader

Read-onlyIdempotent

Read Netlify teams, individual team details, and team environment variables for inspection without modifying resources.

Instructions

Select and run one of the following Netlify read operations (read-only) get-teams, get-team, get-team-env-vars

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
selectSchemaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedInput schema / properties / selectSchema / anyOf
      Previous value: -[
      -  {
      -    "additionalProperties": false,
      -    "properties": {
      -      "aiAgentName": {
      -        "type": "string"
      -      },
      -      "llmModelName": {
      -        "type": "string"
      -      },
      -      "operation": {
      -        "const": "get-teams",
      -        "type": "string"
      -      },
      -      "params": {
      -        "additionalProperties": false,
      -        "properties": {},
      -        "type": "object"
      -      }
      -    },
      -    "required": [
      -      "operation"
      -    ],
      -    "type": "object"
      -  },
      -  {
      -    "additionalProperties": false,
      -    "properties": {
      -      "aiAgentName": {
      -        "type": "string"
      -      },
      -      "llmModelName": {
      -        "type": "string"
      -      },
      -      "operation": {
      -        "const": "get-team",
      -        "type": "string"
      -      },
      -      "params": {
      -        "additionalProperties": false,
      -        "properties": {
      -          "teamId": {
      -            "type": "string"
      -          }
      -        },
      -        "required": [
      -          "teamId"
      -        ],
      -        "type": "object"
      -      }
      -    },
      -    "required": [
      -      "operation"
      -    ],
      -    "type": "object"
      -  }
      -]New value: +[
      +  {
      +    "properties": {
      +      "aiAgentName": {
      +        "type": "string"
      +      },
      +      "llmModelName": {
      +        "type": "string"
      +      },
      +      "operation": {
      +        "const": "get-teams",
      +        "type": "string"
      +      },
      +      "params": {
      +        "properties": {},
      +        "type": "object"
      +      }
      +    },
      +    "required": [
      +      "operation"
      +    ],
      +    "type": "object"
      +  },
      +  {
      +    "properties": {
      +      "aiAgentName": {
      +        "type": "string"
      +      },
      +      "llmModelName": {
      +        "type": "string"
      +      },
      +      "operation": {
      +        "const": "get-team",
      +        "type": "string"
      +      },
      +      "params": {
      +        "properties": {
      +          "teamId": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "teamId"
      +        ],
      +        "type": "object"
      +      }
      +    },
      +    "required": [
      +      "operation"
      +    ],
      +    "type": "object"
      +  },
      +  {
      +    "properties": {
      +      "aiAgentName": {
      +        "type": "string"
      +      },
      +      "llmModelName": {
      +        "type": "string"
      +      },
      +      "operation": {
      +        "const": "get-team-env-vars",
      +        "type": "string"
      +      },
      +      "params": {
      +        "properties": {
      +          "envVarKey": {
      +            "type": "string"
      +          },
      +          "teamId": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "teamId"
      +        ],
      +        "type": "object"
      +      }
      +    },
      +    "required": [
      +      "operation"
      +    ],
      +    "type": "object"
      +  }
      +]
  2. Addedv1.0.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, and the description merely restates 'read-only' without adding new behavioral context. It discloses nothing about what the operations return, pagination, or how the optional envVarKey affects results.

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

Conciseness4/5

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

A single efficiently front-loaded sentence naming the operation set, with no filler. It is appropriately sized for a thin multiplexer wrapper, though it is arguably too terse to guide use.

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

Completeness2/5

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

With no output schema and a nested anyOf parameter wrapper, the description should clarify what each operation returns and which parameters belong to which variant. It omits all of that, leaving the agent to reverse-engineer operation behavior from schema consts.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no meaning for any parameter. It never mentions required teamId, optional envVarKey, or the aiAgentName/llmModelName fields. While the schema's anyOf variants structurally imply required fields, the prose contributes nothing beyond what is already structured.

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

Purpose4/5

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

The description states a specific resource (Netlify team services) and enumerates the three read operations it multiplexes (get-teams, get-team, get-team-env-vars). The name and text distinguish it from user/deploy/project readers, so an agent can tell roughly what it covers, though it never explains how the three sub-operations differ in purpose.

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

Usage Guidelines2/5

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

It says the tool runs one of three read operations but gives no guidance on when to choose each operation, what prerequisites apply, or when to prefer a sibling reader. The agent must infer everything about operation selection from the operation names alone.

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