web_contents
Extract the full text of specific URLs, with optional highlights and a summary. Use when you already know which pages you need, rather than searching for them.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/web-contents.md
What web_contents does on Mcp Knowledge
AI agents use web_contents to create or update resources in Mcp Knowledge, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Knowledge environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
urls | array | Yes | The URLs to extract |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
summary | boolean | — | Also return a short summary of each page |
highlights | boolean | — | Also return the most relevant excerpts |
Parameters from the server's own tool schema.
Why web_contents is rated Medium
An AI agent can call web_contents faster than any human can review: one bad instruction and it creates or modifies resources in Mcp Knowledge by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs web_contents safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For web_contents, this is the rule to start with:
web_contents stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every web_contents call is checked against it from then on.
Questions about web_contents
Extract the full text of specific URLs, with optional highlights and a summary. Use when you already know which pages you need, rather than searching for them. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
web_contents accepts 4 parameters: urls, async, summary, highlights. Required: urls. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for web_contents: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.
web_contents is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the web_contents rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for web_contents. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
web_contents is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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