Record development context to memory. Call IMMEDIATELY after file changes. WHEN TO USE: - After making code changes (edits, additions, deletions) - When solving bugs or implementing features - Documenting design decisions or learning - Capturing important development work WHEN NOT TO USE: - Do NO...
AI agents use record_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.
This tool creates or modifies persistent memory records of development context. While the data being recorded is metadata about development activities (not the actual code files), the act of writing to a memory store and the potential for an agent to record inaccurate or misleading context about code changes makes it a Write operation.
From the tool's definition Tool description states 'Record development context to memory' and is designed to be called 'IMMEDIATELY after file changes' to capture 'code changes (edits, additions, deletions)' and 'development work'.
Documented attack patterns abuse exactly the kind of access record_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 record_context:
{
"version": "1",
"default": "deny",
"tools": {
"record_context": {
"limits": [
{
"counter": "record_context_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}record_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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Record development context to memory. Call IMMEDIATELY after file changes. WHEN TO USE: - After making code changes (edits, additions, deletions) - When solving bugs or implementing features - Documenting design decisions or learning - Capturing important development work WHEN NOT TO USE: - Do NOT record query processes or search operations - Do NOT record information retrieval (use semantic_search instead) - Do NOT record when just looking up existing information WORKFLOW: Edit files → semantic_search → record_context (or update_context if similar exists) → Respond Auto-detects: Git changes, context type, quality scores. Smart update for duplicates (v2.4.9). 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 record_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.
record_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 record_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 record_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.
record_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.