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update_service

Modify service attributes like name, description, labels, upstream configuration, and plugins using the APISIX-MCP server to maintain and enhance API gateway services.

Instructions

Update specific attributes of an existing service

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoservice id
serviceNoservice configuration object

Implementation Reference

  • The inline handler function for the 'update_service' tool. It calls makeAdminAPIRequest to perform a PATCH request on `/services/${args.id}` with the provided service attributes. This constitutes the core logic of the tool.
    server.tool("update_service", "Update specific attributes of an existing service", UpdateServiceSchema.shape, async (args) => {
      return await makeAdminAPIRequest(`/services/${args.id}`, "PATCH", args.service);
    });
  • Registration of the 'update_service' tool using server.tool(), including description, input schema (UpdateServiceSchema.shape), and the handler function.
    server.tool("update_service", "Update specific attributes of an existing service", UpdateServiceSchema.shape, async (args) => {
      return await makeAdminAPIRequest(`/services/${args.id}`, "PATCH", args.service);
    });
  • Supporting utility function `makeAdminAPIRequest` that performs HTTP requests to the APISIX Admin API, handling both success and error responses in MCP format. Used by the update_service handler.
    export async function makeAdminAPIRequest(
      path: string,
      method: string = "GET",
      data?: object
    ): Promise<CallToolResult> {
      const baseUrl = `${APISIX_SERVER_HOST}:${APISIX_ADMIN_API_PORT}${APISIX_ADMIN_API_PREFIX}`;
      const url = `${baseUrl}${path}`;
    
      try {
        const response = await axios({
          method,
          url,
          data,
          headers: {
            "X-API-KEY": APISIX_ADMIN_KEY,
            "Content-Type": "application/json",
          },
        });
    
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(response.data, null, 2),
            },
          ],
        };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          console.error(`Request failed: ${method} ${url}`);
          console.error(
            `Status: ${error.response?.status}, Error: ${error.message}`
          );
    
          if (error.response?.data) {
            try {
              const stringifiedData = JSON.stringify(error.response.data);
              console.error(`Response data: ${stringifiedData}`);
            } catch {
              console.error(`Response data: [Cannot parse as JSON]`);
            }
          }
    
          return {
            isError: true,
            content: [
              {
                type: "text",
                text: JSON.stringify(
                  `Status: ${error.response?.status}\nMessage: ${error.message}
    Data:\n${JSON.stringify(error.response?.data || {}, null, 2)}`,
                  null,
                  2
                ),
              },
            ],
          };
        } else {
          return {
            isError: true,
            content: [
              {
                type: "text",
                text: JSON.stringify(error, null, 2),
              },
            ],
          };
        }
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'update' which implies mutation, but doesn't disclose behavioral traits such as required permissions, whether changes are reversible, rate limits, or what happens to unspecified attributes (e.g., partial vs. full update). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence with zero waste: 'Update specific attributes of an existing service'. It's front-loaded and appropriately sized for the tool's complexity, earning its place by clarifying the scope of the update.

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?

Given the complexity (mutation tool with nested configuration objects), no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects, error conditions, or return values, leaving significant gaps for an AI agent to understand how to invoke it correctly in context.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents both parameters ('id' and 'service'). The description adds no meaning beyond the schema—it doesn't explain parameter relationships, constraints, or examples. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

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

Purpose3/5

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

The description states the verb ('update') and resource ('service') with the qualifier 'specific attributes of an existing service', which clarifies it's a partial update rather than a full replacement. However, it doesn't differentiate from sibling tools like 'update_route' or 'update_upstream'—it only tells what it does, not how it differs from other update operations in the system.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing a service ID), exclusions, or comparisons to sibling tools like 'create_service' or other update operations. Usage is implied by the name alone, with no explicit context for selection.

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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