Skip to main content
Glama

load-official-blueprint

Load predefined blueprints on Flux MCP server by specifying blueprintName and processId, enabling AI-powered creation, running, and testing of code and handlers in Arweave OS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blueprintNameYes
processIdYes

Implementation Reference

  • src/mcp.ts:217-231 (registration)
    Registration of the 'load-official-blueprint' tool including name, description, Zod input schema, and inline handler function.
    this.server.tool(
      "load-official-blueprint",
      "load an official blueprint in an existing AO process",
      { blueprintName: z.string(), processId: z.string() },
      async ({ blueprintName, processId }) => {
        const result = await addBlueprint(
          blueprintName,
          processId,
          this.signer
        );
        return {
          content: [{ type: "text", text: cleanOutput(result) }],
        };
      }
    );
  • The handler function that implements the tool logic by invoking addBlueprint and formatting the response.
    async ({ blueprintName, processId }) => {
      const result = await addBlueprint(
        blueprintName,
        processId,
        this.signer
      );
      return {
        content: [{ type: "text", text: cleanOutput(result) }],
      };
    }
  • Input schema using Zod for blueprintName and processId parameters.
    { blueprintName: z.string(), processId: z.string() },
  • Core helper function that fetches the official blueprint Lua code from GitHub and loads it into the specified AO process.
    export async function addBlueprint(
      blueprintName: string,
      processId: string,
      signer: any
    ) {
      const url = `https://raw.githubusercontent.com/permaweb/aos/refs/heads/main/blueprints/${blueprintName}.lua`;
      const code = await fetchBlueprintCode(url);
      const result = await runLuaCode(code, processId, signer);
      return result;
    }
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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?

Tool has no description.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/asrvd/flux'

If you have feedback or need assistance with the MCP directory API, please join our Discord server