Computer-Use Agents API
Server Details
Run and manage H Company's Computer-Use Agents from any MCP client.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- hcompai/hai-agents-python
- GitHub Stars
- 31
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.2/5 across 6 of 6 tools scored.
Each tool targets a unique action: cancel, list, run, send message, share, or wait for sessions/agents. No overlap.
All tool names follow the verb_noun pattern consistently (e.g., cancel_session, list_agents).
Six tools is an ideal number for managing agent sessions and agent listing, not too few or too many.
Covers full lifecycle: create/run, interact (send_message), wait for results, cancel, share, and list agents. No obvious gaps.
Available Tools
6 toolscancel_sessionAInspect
Cancel a session; a no-op if it does not exist or already finished.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It states the operation and idempotency, but does not mention permissions, side effects (e.g., resource release), or what happens to a running session beyond cancellation. Adequate but leaves some gaps.
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?
Single sentence, 13 words, front-loaded with the verb and resource. Every word earns its place, no fluff.
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 (1 param, no nested objects, has output schema). Description covers purpose and idempotency. Could mention output structure or side effects, but given low complexity, it is mostly complete.
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?
Only one parameter (session_id) with no description in the schema. The description does not elaborate on its format, constraints, or meaning beyond what the name implies. Since schema coverage is 0%, the description should compensate, but it fails to add value.
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?
Name and description clearly state the action (cancel) and resource (session). Idempotency detail distinguishes it from siblings, all of which are different operations.
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?
The description explicitly says 'Cancel a session' and clarifies that it's a no-op if the session does not exist or is already finished, giving clear context on when to use it. No explicit alternatives are needed as no sibling tool performs cancellation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_agentsBInspect
List agents the caller can run: their org's agents plus the public h/ ones.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| size | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. However, it does not disclose pagination behavior, rate limits, required permissions, or any side effects. It only states 'List agents' without further behavioral context.
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?
The description is a single concise sentence that communicates the core purpose. It is front-loaded and avoids unnecessary words. However, it could include parameter info without losing conciseness.
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?
Given no annotations, low parameter coverage, and sibling tools like 'run_agent', the description is incomplete. It does not explain what the output contains, pagination, or how to interpret results. The output schema exists but does not fully compensate for missing behavioral context.
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 has two parameters (page, size) with defaults, but the description does not explain their meaning or usage. Schema description coverage is 0%, and the description fails to compensate, providing no parameter semantics.
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 agents the caller can run, specifying the scope as their org's agents and public 'h/' ones. It uses a specific verb ('list') and resource ('agents'), distinguishing it from sibling tools like 'run_agent' or 'cancel_session'.
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?
The description implies usage for listing available agents before running them, but does not explicitly state when to use this tool versus alternatives like 'run_agent'. No guidance on prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_agentBInspect
Start an agent on a task; return the answer or a session handle to wait on. agent from list_agents.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | ||
| agent | Yes | ||
| max_steps | No | ||
| max_time_s | No | ||
| idempotency_key | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states the basic action and outcome, without mentioning potential side effects, resource usage, authentication needs, or error conditions.
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?
The description is two sentences long, immediately stating the purpose and key outcome. Every word adds value, and it is front-loaded for quick comprehension.
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?
Despite having an output schema, the description fails to explain when to expect an answer versus a session handle, how parameters like max_steps or max_time_s affect behavior, or how this tool interacts with others like wait_for_session.
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 description adds meaning only for the 'agent' parameter by referring to list_agents. The other four parameters (task, max_steps, max_time_s, idempotency_key) are not described, and schema coverage is 0%, leaving their purpose unclear.
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 uses the verb 'start' with the resource 'agent on a task', which clearly indicates the action. It also mentions returning an answer or session handle, and references 'agent from list_agents', which distinguishes it from sibling tools like list_agents and wait_for_session.
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?
The description implicitly suggests use after list_agents by referencing it, but does not explicitly state when to use this tool versus alternatives like send_message or wait_for_session. No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageBInspect
Send a follow-up message to a running session.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action 'send' but does not explain blocking behavior, return values, side effects, or any permissions needed. This is insufficient for a mutation tool.
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?
The description is a single sentence that conveys the core purpose efficiently. It is front-loaded and contains no unnecessary words, though it could be expanded with behavioral details without losing conciseness.
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?
Despite having an output schema, the description lacks essential context like whether the call is blocking, what happens if the session is not running, or how to interpret the response. For a tool with no annotations, this is incomplete.
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 description coverage is 0%, and the description adds almost no meaning beyond parameter names. 'message' and 'session_id' are self-explanatory from their names, but no format, constraints, or usage hints are provided.
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 verb 'send', the resource 'message', and the context 'follow-up to a running session'. It distinguishes this tool from siblings like cancel_session or run_agent because no other sibling sends messages.
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?
The description specifies that the tool is for sending a follow-up message to a 'running session', implying prerequisite of having an active session. However, it does not explicitly mention when not to use it or provide alternative tools for different scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wait_for_sessionBInspect
Poll a session: with wait long-poll for the answer, else return the current snapshot.
| Name | Required | Description | Default |
|---|---|---|---|
| wait | No | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions long-polling and snapshot return but omits critical details like blocking behavior, timeout, error conditions, or safety. The read-only nature is implied but not explicit.
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?
The description is a single sentence with no fluff, using backticks for code formatting. It's appropriately concise, though it could benefit from a bit more structure to separate modes.
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?
With an output schema present, the return shape is covered. However, the description lacks context on prerequisites, error handling, and when to use each mode. The minimal description is adequate for a simple tool but leaves room for improvement.
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 description coverage is 0%, so the description must compensate. It explains the 'wait' parameter (long-poll vs snapshot) but fails to describe the 'session_id' parameter or its format. Only one of two parameters is addressed, leaving a significant gap.
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 uses a specific verb 'Poll a session' and distinguishes two modes (long-poll vs snapshot), clearly identifying the resource and action. However, it doesn't differentiate from siblings like cancel_session or send_message, though those are distinct enough.
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?
The description implies when to use the tool (to get session answer or snapshot) but lacks explicit guidance on when not to use it or alternatives. No exclusions are mentioned, but the behavioral difference is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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