Skip to main content
Glama

create_project

Set up a named web project with base URL and crawl limits, saved to disk for reuse in testing and authentication workflows.

Instructions

Create a persistent testing project: a named website/web-app target with its base URL and crawl limits, saved to disk and reused by crawl_project, test_project, and authenticated sessions. Returns the stored project config. Create this first, then attach auth (set_form_login / set_basic_auth / set_cookies) and run tests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesUnique project name (e.g., 'mysite')
base_urlYesBase URL of the website (e.g., 'https://example.com')
max_depthNoMax crawl depth (default: 3)
max_pagesNoMax pages to crawl (default: 20)
screenshot_dirNoAbsolute path to save screenshots (e.g. '/home/user/myproject/e2e_testing'). Defaults to built-in data/screenshots/ if omitted.
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses that the project is persistent (saved to disk) and returns the stored config. It doesn't mention behavior on duplicate names or error conditions, but the core behavior is well-covered.

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?

Two sentences: the first is front-loaded with the core purpose and key details, the second provides immediate action guidance. Every word earns its place; no repetition or fluff.

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

Completeness5/5

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

Given 5 parameters, no output schema, and no annotations, the description provides a complete picture: what the tool creates, how it's used in the workflow, and what it returns. It explains the lifecycle and integration with sibling tools thoroughly.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the parameter purpose in context (e.g., 'crawl limits' for max_depth/max_pages, 'reused by crawl_project, test_project' for the project concept). This goes beyond the schema's individual field descriptions.

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

Purpose5/5

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

The description clearly states the tool creates a persistent testing project for a website/web-app target, specifying it's saved to disk and reused by other tools. It distinguishes itself from siblings like crawl_project and test_project by emphasizing its role as the initial setup step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Create this first, then attach auth... and run tests', providing clear sequential guidance. It also lists specific sibling tools for subsequent steps (set_form_login, set_basic_auth, set_cookies), helping the agent understand when to use this tool versus alternatives.

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/segentic-lab/periscope-mcp'

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