Skip to main content
Glama

n8n_list_projects

Retrieve all projects from your n8n instance to manage workflows and monitor executions.

Instructions

List all projects

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Actual implementation of the listProjects method which calls the n8n API.
    async listProjects(): Promise<any> {
      const response = await this.client.get('/projects');
      return response.data;
    }
  • Handler logic in the MCP server switch statement that invokes the n8n client method.
    case 'n8n_list_projects': {
      const result = await n8nClient.listProjects();
      return {
        content: [{ type: 'text', text: formatResponse(result) }],
      };
    }
  • src/index.ts:819-826 (registration)
    Tool registration in the MCP tool list.
    {
      name: 'n8n_list_projects',
      description: 'List all projects',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
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. 'List all projects' implies an unfiltered read operation but fails to disclose pagination behavior, rate limits, authentication requirements, or the structure/format of returned project data. The scope of 'all' is undefined (e.g., across all workspaces or scoped to credentials).

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?

The three-word description is extremely efficient with zero redundancy. However, given the absence of annotations, output schema, and behavioral details, the description verges on under-specification rather than optimal conciseness—it could afford additional sentences explaining return values or usage context.

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 zero parameters and a simple read-only intent, the description provides minimally viable information to invoke the tool. However, with no output schema available, the description should have described the return structure (fields, format) or filtering limitations to be complete.

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?

Input schema contains zero parameters. Per rubric guidelines, 0 parameters establishes a baseline score of 4. The description does not need to compensate for missing schema documentation.

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 a specific verb (List) and resource (projects), providing clear minimal purpose. However, it lacks scope context (what defines a project in n8n vs workflows/executions) and does not differentiate from the numerous sibling 'list' operations (list_workflows, list_users, etc.) beyond the resource name.

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 provided on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., admin permissions) or when to prefer this over project-specific getters like n8n_get_workflow (if projects contain workflows). The agent receives no decision-making context.

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

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/Shravan1610/n8n-mcp-server'

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