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listProviders

Retrieve all configured language model providers and their available models using the MindBridge MCP Server to enable efficient model selection and orchestration.

Instructions

List all configured LLM providers and their available models

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The inline async handler function for the 'listProviders' tool. It fetches all available providers, their models, and reasoning support using ProviderFactory methods, formats as JSON, and returns as MCP content or error.
    async () => {
      try {
        const providers = this.providerFactory.getAvailableProviders();
        const result: Record<string, {
          models: string[];
          supportsReasoning: boolean;
        }> = {};
    
        for (const provider of providers) {
          result[provider] = {
            models: this.providerFactory.getAvailableModelsForProvider(provider),
            supportsReasoning: this.providerFactory.supportsReasoningEffort(provider)
          };
        }
    
        return {
          content: [{ type: 'text', text: JSON.stringify(result, null, 2) }]
        };
      } catch (error) {
        return {
          content: [{ type: 'text', text: `Error: ${error instanceof Error ? error.message : 'An unknown error occurred'}` }],
          isError: true
        };
      }
    }
  • src/server.ts:82-111 (registration)
    Registers the 'listProviders' tool with the MCP server using this.tool(). Includes empty schema {} and inline handler. No input params required.
    // Register listProviders tool
    this.tool('listProviders',
      'List all configured LLM providers and their available models',
      {},
      async () => {
        try {
          const providers = this.providerFactory.getAvailableProviders();
          const result: Record<string, {
            models: string[];
            supportsReasoning: boolean;
          }> = {};
    
          for (const provider of providers) {
            result[provider] = {
              models: this.providerFactory.getAvailableModelsForProvider(provider),
              supportsReasoning: this.providerFactory.supportsReasoningEffort(provider)
            };
          }
    
          return {
            content: [{ type: 'text', text: JSON.stringify(result, null, 2) }]
          };
        } catch (error) {
          return {
            content: [{ type: 'text', text: `Error: ${error instanceof Error ? error.message : 'An unknown error occurred'}` }],
            isError: true
          };
        }
      }
    );
  • ProviderFactory method used by listProviders handler to get the list of configured provider names.
    public getAvailableProviders(): string[] {
      return Array.from(this.providers.keys());
    }
  • ProviderFactory method used to fetch available models for a specific provider instance.
    public getAvailableModelsForProvider(providerName: string): string[] {
      const provider = this.getProvider(providerName);
      return provider ? provider.getAvailableModels() : [];
    }
  • ProviderFactory method used to check if a provider supports reasoning effort parameter.
    public supportsReasoningEffort(providerName: string): boolean {
      const provider = this.getProvider(providerName);
      return provider ? provider.supportsReasoningEffort() : false;
    }
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the tool's behavior (listing providers and models) but doesn't mention important traits like whether this requires authentication, rate limits, pagination behavior, or what format the output takes. The description is accurate but lacks operational context.

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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information immediately.

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

Completeness3/5

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

For a zero-parameter listing tool with no output schema, the description provides the core purpose but lacks information about output format, authentication requirements, or error conditions. While adequate for basic understanding, it doesn't fully prepare an agent for operational use without additional context.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the empty parameter set. The description appropriately doesn't add parameter information beyond what's already covered, maintaining the baseline for zero-parameter tools.

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 specific action ('List all configured LLM providers and their available models') with precise verb+resource combination. It distinguishes from sibling tools like 'getSecondOpinion' and 'listReasoningModels' by focusing on provider configuration rather than reasoning models or second opinions.

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

Usage Guidelines3/5

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

The description implies usage context (when you need to see configured providers and models) but doesn't explicitly state when to use this tool versus alternatives like 'listReasoningModels'. No explicit exclusions or prerequisites are mentioned, leaving usage guidance at an implied level.

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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