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dewanshparashar

Arbitrum MCP Server

search_chains

Find Arbitrum chains by name, chain ID, or partial name match when you have incomplete information about the network.

Instructions

Search for Arbitrum chains by name, chain ID, or partial name match. Perfect for finding chains when you have incomplete information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (chain name like 'Xai', 'Arbitrum One', chain ID like '42161', or partial name)

Implementation Reference

  • MCP tool handler that executes search_chains by calling ChainLookupService.searchChains with the provided query and formats the results as text response.
    case "search_chains":
      const searchResults = await this.chainLookupService.searchChains(
        args.query as string
      );
      return {
        content: [
          {
            type: "text",
            text:
              searchResults.length > 0
                ? `Found chains:\n${searchResults
                    .map((c) => `${c.name} (ID: ${c.chainId})`)
                    .join("\n")}`
                : `No chains found matching "${args.query}"`,
          },
        ],
      };
  • Input schema and metadata definition for the search_chains tool, specifying the required 'query' parameter.
      name: "search_chains",
      description:
        "Search for Arbitrum chains by name, chain ID, or partial name match. Perfect for finding chains when you have incomplete information.",
      inputSchema: {
        type: "object" as const,
        properties: {
          query: {
            type: "string",
            description:
              "Search query (chain name like 'Xai', 'Arbitrum One', chain ID like '42161', or partial name)",
          },
        },
        required: ["query"],
      },
    },
  • Core helper function implementing the chain search logic: filters cached OrbitChainData by name, slug, or exact chain ID match.
    async searchChains(query: string): Promise<OrbitChainData[]> {
      await this.ensureChainsData();
      
      const searchQuery = query.toLowerCase().trim();
      
      return this.chainsData.filter(chain => 
        chain.name.toLowerCase().includes(searchQuery) ||
        chain.slug?.toLowerCase().includes(searchQuery) ||
        chain.chainId.toString() === searchQuery
      );
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool is 'perfect for finding chains when you have incomplete information,' which implies a search operation, but it does not disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, consisting of two concise sentences that directly convey the tool's purpose and usage context without any wasted words. Every sentence earns its place by providing essential information efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a search function with no output schema and no annotations), the description is incomplete. It lacks details on behavioral aspects like safety, output format, or error handling, which are crucial for an AI agent to use the tool effectively. The description does not compensate for the absence of structured data, leaving gaps in contextual understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'query' parameter well-documented in the schema. The description adds minimal value by reiterating that searches can be by 'name, chain ID, or partial name match,' which is already implied in the schema's description. Since schema coverage is high, the baseline score of 3 is appropriate, as the description does not significantly enhance parameter understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('search for Arbitrum chains') and resources ('by name, chain ID, or partial name match'), distinguishing it from sibling tools like 'list_chains' by emphasizing search functionality rather than listing. It explicitly mentions the types of queries accepted, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use this tool ('when you have incomplete information'), but it does not explicitly mention when not to use it or name specific alternatives like 'list_chains' for broader queries. This gives good guidance but lacks explicit exclusions or named sibling comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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