Skip to main content
Glama
OnStartups

Agent.ai MCP Server

by OnStartups

openclaw_chat_completion

Send a user message to an OpenClaw instance and receive the assistant's reply via an OpenAI-compatible API. Supports multi-turn conversations and streaming.

Instructions

Send a chat completion request to an OpenClaw instance via the OpenAI-compatible API. Returns the assistant's response text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_ipYesIP address or hostname of the OpenClaw instance (e.g., 167.71.242.214). Do not include https:// prefix.
auth_tokenYesBearer token for authenticating with the OpenClaw Gateway.
messageNoThe user message to send. For multi-turn conversations, use 'Messages JSON' instead or in addition.
messages_jsonNoOptional JSON array of prior messages for multi-turn conversations. Format: [{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}]. If 'Message' is also provided, it is appended as the latest user turn.
modelNoModel identifier. Format: 'openclaw:<agentId>' or 'agent:<agentId>'. Default: openclaw:main.openclaw:main
agent_idNoOpenClaw agent ID sent via x-openclaw-agent-id header. Default: main.main
session_keyNoOptional session key for conversation continuity. Requests with the same session key share the same agent session on the OpenClaw instance.
streamNoUse Server-Sent Events (SSE) streaming for the response.
timeoutNoRequest timeout in seconds. Default: 120.120
output_variable_nameYesVariable name for the result. Access response with {{openclaw_result.response_text}}.openclaw_result
Behavior2/5

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

No annotations provided, so description must disclose behavioral traits. It only states basic send/receive behavior, omitting side effects, streaming implications, or auth specifics beyond parameter description.

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 concise sentences with front-loaded purpose. No unnecessary words. Efficient and clear.

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?

Despite 10 parameters (3 required), no output schema, and no annotations, the description is too brief. Lacks guidance on session key, streaming, timeout, or output variable usage for a complex tool.

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?

Schema coverage is 100% via context signals, so baseline is 3. Description adds minimal value beyond schema (e.g., return text). No additional semantic enrichment.

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?

Description clearly states the verb 'Send', resource 'chat completion request to OpenClaw instance', and return 'assistant's response text'. This distinguishes it from sibling tools like 'rest_call' or 'invoke_llm'.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives (e.g., 'invoke_llm' or 'rest_call'). Missing context for preferred scenarios or exclusions.

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/OnStartups/agentai-mcp-server'

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