Get definition + caller/callee counts for multiple symbols in one call. Replaces N get_context calls when an agent needs to look up several symbols at once. Default compact mode returns only counts; pass compact=false for full neighbor lists.
AI agents call batch_context to retrieve information from GraphHub without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
batch_context retrieves and queries metadata about code symbols (definitions, caller/callee relationships) without modifying any data or triggering code execution. This is a read operation similar to search/fetch functions. The tool returns analysis of an existing knowledge graph but does not alter state, run arbitrary code, or have destructive side effects.
From the tool's definition Tool description states it 'Get definition + caller/callee counts for multiple symbols' with options for 'full neighbor lists'. No write, delete, execute, or financial operations described.
Risk signalsBulk/mass operation — affects multiple targets
Documented attack patterns abuse exactly the kind of access batch_context gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and GraphHub, and nothing reaches the server without passing your rules. This is the rule we recommend for batch_context:
{
"version": "1",
"default": "deny",
"tools": {
"batch_context": {}
}
}batch_context is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Get definition + caller/callee counts for multiple symbols in one call. Replaces N get_context calls when an agent needs to look up several symbols at once. Default compact mode returns only counts; pass compact=false for full neighbor lists. It is categorised as a Read tool in the GraphHub MCP Server, which means it retrieves data without modifying state.
Register the GraphHub MCP server in PolicyLayer and add a rule for batch_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 GraphHub. Nothing to install.
batch_context is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the batch_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 batch_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.
batch_context is provided by the GraphHub MCP server (slnquangtran/graph-hub). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from GraphHub, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
32 GraphHub tools catalogued and risk-classified — across an index of 43,000+ MCP servers.