List every project in an organization, with each project's ID, name, and slug. Use this to resolve a project ID before calling project-scoped tools. 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 |
|---|---|---|---|
| org_id | Yes | Organization ID whose projects to list |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / org_id / descriptionPrevious value: -"Organization ID"New value: +"Organization ID whose projects to list"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations: the authentication requirement and failure mode on OAuth connections. It also clarifies the scope ('every project' in an organization). The readOnlyHint and idempotentHint are consistent with the 'List' operation, so no contradiction.
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 cover the function, output, usage, and a critical caveat. Every sentence earns its place with no waste or redundancy.
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?
The tool is simple (one parameter, no output schema) and the description covers the operation, return fields, usage context, and authentication caveat. This is complete for an agent to select and invoke the tool correctly.
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?
Schema coverage is 100% and the description includes the org_id parameter in context ('in an organization'). The description does not add deeper semantic details beyond what the schema already provides, so a baseline of 3 is appropriate.
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?
The description clearly states the tool lists every project in an organization and specifies the returned fields (ID, name, slug). It distinguishes itself from sibling tools by being specifically for projects and by noting its role in resolving project IDs for project-scoped tools.
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?
Explicitly instructs when to use the tool ('before calling project-scoped tools') and provides a critical caveat about authentication requirements (admin API key required, fails on OAuth). This gives clear usage direction and boundaries.
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.