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akave-ai

Akave MCP Server

by akave-ai

put_object

Store data objects in cloud storage buckets using the Akave MCP Server. Upload files or content by specifying bucket name, object key, and content body for S3-compatible storage operations.

Instructions

Put object into a bucket

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesObject content
bucketYesBucket name
keyYesObject key

Implementation Reference

  • MCP tool handler for 'put_object' that invokes the S3Client's putObject method and returns a success response.
    async ({ bucket, key, body }: PutObjectParams) => {
      await this.s3Client.putObject(bucket, key, body);
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify({ success: true }),
          },
        ],
      };
    }
  • Zod input schema definition for the 'put_object' tool parameters (bucket, key, body).
    {
      bucket: z.string().describe("Bucket name"),
      key: z.string().describe("Object key"),
      body: z.string().describe("Object content"),
    },
  • src/server.ts:135-154 (registration)
    Registration of the 'put_object' tool on the MCP server, including name, description, input schema, and handler.
    this.server.tool(
      "put_object",
      "Put object into a bucket",
      {
        bucket: z.string().describe("Bucket name"),
        key: z.string().describe("Object key"),
        body: z.string().describe("Object content"),
      },
      async ({ bucket, key, body }: PutObjectParams) => {
        await this.s3Client.putObject(bucket, key, body);
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({ success: true }),
            },
          ],
        };
      }
    );
  • Helper method in S3Client class that executes the AWS S3 PutObjectCommand to store the object.
    async putObject(bucket: string, key: string, body: string) {
      const command = new PutObjectCommand({
        Bucket: bucket,
        Key: key,
        Body: body,
      });
      await this.client.send(command);
    }
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 implies a write operation ('Put') but doesn't disclose behavioral traits such as whether it overwrites existing objects, requires specific permissions, handles errors, or has rate limits. This leaves critical gaps for safe invocation.

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. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary detail.

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 no annotations and no output schema, the description is incomplete for a mutation tool. It lacks details on behavior, return values, error handling, and sibling differentiation, making it inadequate for informed use despite the concise structure.

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 already documents all parameters (body, bucket, key). The description adds no meaning beyond this, as it doesn't explain parameter interactions or usage nuances. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Put object into a bucket' states a clear verb ('Put') and resource ('object'), but it's vague about what 'Put' entails—it could mean upload, create, or replace. It doesn't distinguish from siblings like 'update_object' or 'copy_object', leaving ambiguity in scope.

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. With siblings like 'update_object' and 'copy_object', the description lacks context on use cases, prerequisites, or exclusions, offering no help in tool 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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