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JFrog MCP Server

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by jfrog

jfrog_list_projects

Retrieve detailed information about all projects within the JFrog platform using this tool. Simplify project management and oversight by accessing comprehensive project data.

Instructions

Get a list of all projects in the JFrog platform with their details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler logic: Fetches all JFrog projects from /access/api/v1/projects endpoint and parses the array response using JFrogProjectSchema.
    export async function getAllProjects() {
      const response = await jfrogRequest("/access/api/v1/projects", {
        method: "GET",
      });
         
      return z.array(accessSchemas.JFrogProjectSchema).parse(response);
    }
  • JFrogProjectSchema: Zod schema defining the structure of a JFrog project, used to parse the API response in getAllProjects().
    export const JFrogProjectSchema = z.object({
      display_name: z.string().describe("Display name of the project"),
      description: z.string().describe("Project description"),
      admin_privileges: z.object({
        manage_members: z.boolean().describe("Whether admin can manage members"),
        manage_resources: z.boolean().describe("Whether admin can manage resources"),
        index_resources: z.boolean().describe("Whether admin can index resources")
      }),
      storage_quota_bytes: z.number().describe("Storage quota in bytes"),
      soft_limit: z.boolean().describe("Whether soft limit is enabled"),
      storage_quota_email_notification: z.boolean().describe("Whether storage quota email notifications are enabled"),
      project_key: z.string().describe("Unique key of the project")
    });
  • tools/access.ts:51-59 (registration)
    Tool registration object: Defines name, description, empty input schema (no args needed), and handler delegating to getAllProjects().
    const listAllProjectsTool = {
      name: "jfrog_list_projects",
      description: "Get a list of all projects in the JFrog platform with their details",
      inputSchema: zodToJsonSchema(z.object({})),
      //outputSchema: zodToJsonSchema(z.object({})),
      handler: async (args: any) => {
        return await getAllProjects();
      }
    };
  • tools/index.ts:13-23 (registration)
    Main tools array: Spreads AccessTools (containing jfrog_list_projects) into the complete list of available tools, imported by MCP server.
    export const tools =[
      ...RepositoryTools,
      ...BuildsTools,
      ...RuntimeTools,
      ...AccessTools,
      ...AQLTools,
      ...CatalogTools,
      ...CurationTools,
      ...PermissionsTools,
      ...ArtifactSecurityTools,
    ];
  • executeTool: Helper dispatcher that finds the tool by name (jfrog_list_projects) and invokes its handler with arguments.
    export async function executeTool(toolName: string, args: any) {
      const tool = tools.find(t => t.name === toolName);
      if (!tool) {
        throw new Error(`Tool ${toolName} not found`);
      }
      return await tool.handler(args);
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets a list' but doesn't clarify if this is a read-only operation, what 'details' include, potential rate limits, pagination behavior, or authentication requirements. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse and understand quickly.

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

Completeness3/5

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

Given the tool has 0 parameters and no output schema, the description adequately covers the basic purpose. However, for a list operation with no annotations, it lacks details on return format, error handling, or behavioral traits, which could hinder an agent's ability to use it effectively in complex scenarios.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately doesn't discuss parameters, focusing on the tool's purpose instead, which aligns well with the schema's completeness.

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 clearly states the verb ('Get') and resource ('list of all projects in the JFrog platform with their details'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'jfrog_get_specific_project' or 'jfrog_list_repositories', which would require mentioning it returns all projects versus a specific one or other resource types.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like needing a comprehensive overview versus filtered results, or prerequisites such as authentication or permissions required to access project lists, leaving the agent without 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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