Save context as a markdown file in the project
Part of the Mcp Context server.
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AI agents use context_save to create or modify resources in Mcp Context. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call context_save repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp Context.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"context_save": {
"limits": [
{
"counter": "context_save_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Mcp Context policy for all 7 tools.
These attack patterns abuse exactly the kind of access context_save gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Save context as a markdown file in the project. It is categorised as a Write tool in the Mcp Context MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Context MCP server in PolicyLayer and add a rule for context_save: 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 Context. Nothing to install.
context_save 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 context_save 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 context_save. 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.
context_save is provided by the Mcp Context MCP server (mcp-context-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 Mcp Context tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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