Update existing memory context to avoid duplicate records. WHEN TO USE: - User explicitly requests to update a previous memory - AI discovers the same bug/issue was already recorded and needs updating - Refining or correcting previously recorded information - Avoiding duplicate memories for the s...
AI agents use update_context to create or update resources in DevMind MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your DevMind MCP environment.
The tool modifies existing memory records by updating their content, which is a reversible write operation. It does not delete data (would be Destructive), execute external code (would be Execute), create financial obligations (would be Financial), or merely retrieve information (would be Read).
From the tool's definition Tool description states it 'Update[s] existing memory context' and is designed for 'refining or correcting previously recorded information' and 'updating' previous memories. These are classic write operations that modify data reversibly.
Documented attack patterns abuse exactly the kind of access update_context gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DevMind MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for update_context:
{
"version": "1",
"default": "deny",
"tools": {
"update_context": {
"limits": [
{
"counter": "update_context_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_context 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.
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Update existing memory context to avoid duplicate records. WHEN TO USE: - User explicitly requests to update a previous memory - AI discovers the same bug/issue was already recorded and needs updating - Refining or correcting previously recorded information - Avoiding duplicate memories for the same problem WORKFLOW: 1. Search for existing related context using semantic_search 2. If found duplicate/related context, use update_context instead of record_context 3. This prevents memory clutter and maintains clean history YOU SHOULD: - Check for existing similar contexts before creating new ones - Update existing context when solving the same problem again - Preserve context history while keeping information current. It is categorised as a Write tool in the DevMind MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the DevMind MCP server in PolicyLayer and add a rule for update_context: 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 DevMind MCP. Nothing to install.
update_context 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 update_context 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 update_context. 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.
update_context is provided by the DevMind MCP server (jochenyang/devmind-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from DevMind MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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13 DevMind MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.