Skip to main content
Glama

colab_process_start

Start a process in a Colab runtime under a lease, with durable output and optional auto-export on exit. Retries only if the request was not submitted, ensuring reliable execution.

Instructions

Start durably under a lease. On connection loss retry only if request_not_submitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoExisting runtime directory under /content. Defaults to /content./content
argvYesNon-empty executable and argument array; no shell parsing, expansion, or pipes.
sessionNoTracked session name. Null is allowed only when exactly one session exists.
environmentNoOptional environment overrides. Values are never returned or journaled.
lease_tokenNoOpaque operation-bound lease from colab_allocation_probe. Null performs a fresh probe.
output_limitNoDurable byte cap for each output stream; defaults to 10,000,000.
export_on_exitNoOptional durable auto-export rules. They poll in the MCP background, survive server restart, and never release the runtime.
Behavior2/5

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

No annotations are provided, so the description carries the full transparency burden. It discloses only the retry condition, which is cryptic ('request_not_submitted') and omits side effects, return value, or error behavior. This is insufficient for an operation that starts a potentially long-running process.

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 description is extremely compact—two short sentences—with no filler words. It front-loads the key concept of durable lease-based start, though the terse phrasing introduces ambiguity that reduces clarity.

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

Completeness2/5

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

For a 7-parameter process-start tool with no output schema and no annotations, the description is far from complete. It omits return value, lifecycle context, concrete retry semantics, and prerequisites beyond 'under a lease,' leaving substantial gaps for an agent.

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

Parameters3/5

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

The input schema provides descriptions for all 7 parameters, achieving 100% coverage. The description adds only a contextual tie to the lease_token parameter, but parameter semantics are largely handled by the schema, matching the baseline.

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 uses a specific verb 'Start' and specifies a durable, lease-based process start, which distinguishes it from less durable alternatives like colab_run_command. However, it does not explicitly name sibling tools, leaving some differentiation implicit.

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

Usage Guidelines3/5

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

The description implies a lease prerequisite and gives a conditional retry rule ('retry only if request_not_submitted'), but it does not clearly state when to use this tool versus alternatives or specify exclusions. The context is minimally helpful but not explicit.

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/anluin/colab-mcp'

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