store_memory

Persist a value across your instances: PUT /memory/{ns}/{key}. Optionally set ttl (seconds, min 60, max 30 days) for auto-eviction. Values survive until evicted or manually deleted.

SERVERGateway SOURCEhttps://wingmanprotocol.com/mcp
Medium RISK CLASS
Category Write
Parameters 63 required
Recommended Rate-limitedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/com-wingmanprotocol-agent-gateway/store-memory.md

What store_memory does on Gateway

AI agents use store_memory to create or update resources in Gateway, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gateway environment.

ParameterTypeRequiredDescription
key string Yes entry name
ttl integer seconds until auto-eviction (60–2_592_000, omit=permanent)
value object Yes any JSON value
handle string
secret string
namespace string Yes logical grouping (e.g. 'projects')

Parameters from the server's own tool schema.

Why store_memory is rated Medium

This tool creates and modifies data in a memory/state store that persists across agent instances. While the operation is reversible (can be deleted or auto-evicted), unauthorized or erroneous writes could corrupt agent state, cause logic errors, or interfere with other agent instances sharing the same namespace.

From the tool's definition Tool description states 'Persist a value' and 'PUT /memory/{ns}/{key}', indicating creation/modification of data in a persistent store. The ability to 'set ttl' for 'auto-eviction' and 'manually deleted' confirms reversible data manipulation.

Risk signalsHandles credentials or secrets (secret)

Questions about store_memory

What does the store_memory tool do? +

Persist a value across your instances: PUT /memory/{ns}/{key}. Optionally set ttl (seconds, min 60, max 30 days) for auto-eviction. Values survive until evicted or manually deleted. It is categorised as a Write tool in the Gateway MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does store_memory accept? +

store_memory accepts 6 parameters: key, ttl, value, handle, secret, namespace. Required: key, value, namespace. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on store_memory? +

Register the Gateway MCP server in PolicyLayer and add a rule for store_memory: 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 Gateway. Nothing to install.

What risk level is store_memory? +

store_memory is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit store_memory? +

Yes. Add a rate_limit block to the store_memory 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.

How do I block store_memory completely? +

Set action: deny in the PolicyLayer policy for store_memory. 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.

What MCP server provides store_memory? +

store_memory is provided by the Gateway MCP server (https://wingmanprotocol.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

More on Gateway, and thousands of servers like it.

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