gala_launchpad_fetch_token_classes_with_supply
Fetch supply metrics for multiple token classes in a single batch query. Returns totalSupply, maxSupply, and totalBurned for each token. Efficient for portfolio analysis.
This record as markdown: /tools/gala-chain-gala-mcp-server/gala-launchpad-fetch-token-classes-with-supply.md
What gala_launchpad_fetch_token_classes_with_supply does on Gala
AI agents call gala_launchpad_fetch_token_classes_with_supply to retrieve information from Gala without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
tokenClasses | array | Yes | Array of TokenClassKey objects to query supply for. |
Parameters from the server's own tool schema.
Why gala_launchpad_fetch_token_classes_with_supply is rated Low
Even though gala_launchpad_fetch_token_classes_with_supply only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs gala_launchpad_fetch_token_classes_with_supply safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gala, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For gala_launchpad_fetch_token_classes_with_supply, this is the rule to start with:
gala_launchpad_fetch_token_classes_with_supply is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gala, apply this rule, and every gala_launchpad_fetch_token_classes_with_supply call is checked against it from then on.
Questions about gala_launchpad_fetch_token_classes_with_supply
Fetch supply metrics for multiple token classes in a single batch query. Returns totalSupply, maxSupply, and totalBurned for each token. Efficient for portfolio analysis. It is categorised as a Read tool in the Gala MCP Server, which means it retrieves data without modifying state.
gala_launchpad_fetch_token_classes_with_supply accepts 1 parameter: tokenClasses. Required: tokenClasses. The full parameter table on this page comes from the server's own tool schema.
Register the Gala MCP server in PolicyLayer and add a rule for gala_launchpad_fetch_token_classes_with_supply: 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 Gala. Nothing to install.
gala_launchpad_fetch_token_classes_with_supply 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 gala_launchpad_fetch_token_classes_with_supply 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 gala_launchpad_fetch_token_classes_with_supply. 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.
gala_launchpad_fetch_token_classes_with_supply is provided by the Gala MCP server (@gala-chain/gala-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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