Create a new project within an organization. Returns the project ID, name, and slug. Issue an API key for the new project separately. Needs an admin API key: organization admin scope is never delegated to a connected app, so this tool fails on an OAuth connection.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Project display name | |
| slug | Yes | URL-safe project slug | |
| org_id | Yes | Organization ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds valuable behavioral detail beyond the annotations: returns project ID/name/slug, requires admin API key, and fails on OAuth connections. No contradiction with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with the core action and return data. Every sentence adds essential information without filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple create operation with no output schema, the description fully covers return values, authentication requirements, failure mode, and the next step. No important gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all three parameters with 100% coverage, so the description does not need to repeat parameter semantics. It adds no per-parameter detail, matching the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it creates a project within an organization, using a specific verb and resource. This distinguishes it from sibling tools like scalix_project_list by the action, and it names the return values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage context: requires an admin API key, will fail on OAuth connections, and includes a follow-up action to issue an API key separately. This gives clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are grouped by service prefix and generally target distinct resources/actions. A few execution surfaces could be confused (sandbox_run vs computer_exec vs fn_invoke; build_create vs fn_deploy vs run_deploy), and storage_list is overloaded for both buckets and objects, but descriptions clarify the boundaries well.
The scalix_ prefix plus snake_case is used throughout, and most tools follow <service>_<verb>_<noun>. Minor deviations like scalix_search, scalix_status, and scalix_usage omit a service-domain qualifier, but the overall pattern is predictable and easy to navigate.
53 tools is a very large surface. While the server covers a broad multi-service cloud platform, the count falls well beyond the 25+ threshold and will likely feel overwhelming; many service areas could reasonably be split into separate servers or trimmed.
Several service lifecycles have obvious gaps: the KV store has get/list/set but no delete, storage has upload/download/list but no delete for objects or buckets, functions have deploy/list/invoke but no delete/update, and cron has create but no list/delete. These missing operations create dead ends for agents managing common resources.
