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tanmay4l

Futarchy MCP Server

by tanmay4l

buyInFailMarket

Purchase tokens in the fail market for a specific proposal, enabling users to trade based on proposal outcomes within the Futarchy protocol on Solana.

Instructions

Buy tokens in the fail market for a proposal

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
proposalIdYesThe ID of the proposal to trade in
amountYesAmount to buy
userYesUser's public key

Implementation Reference

  • Full registration of the 'buyInFailMarket' MCP tool, including name, description, Zod input schema (proposalId: string, amount: number, user: string), and handler function that calls apiClient.buyInFailMarket and returns formatted response or error.
    server.tool(
      "buyInFailMarket",
      "Buy tokens in the fail market for a proposal",
      {
        proposalId: z.string().describe("The ID of the proposal to trade in"),
        amount: z.number().describe("Amount to buy"),
        user: z.string().describe("User's public key"),
      },
      async ({ proposalId, amount, user }) => {
        try {
          const response = await apiClient.buyInFailMarket(proposalId, amount, user);
          
          if (!response.success) {
            return {
              content: [
                {
                  type: "text" as const,
                  text: response.error || 'Unknown error',
                },
              ],
              isError: true,
            };
          }
          
          return {
            content: [
              {
                type: "text" as const,
                text: JSON.stringify(response.data, null, 2),
              },
            ],
          };
        } catch (error: any) {
          return {
            content: [
              {
                type: "text" as const,
                text: `Error buying in fail market: ${error.message || 'Unknown error'}`,
              },
            ],
            isError: true,
          };
        }
      }
    );
  • Zod schema for tool inputs: proposalId (string), amount (number), user (public key string).
    {
      proposalId: z.string().describe("The ID of the proposal to trade in"),
      amount: z.number().describe("Amount to buy"),
      user: z.string().describe("User's public key"),
    },
  • Handler function that executes the tool: calls apiClient.buyInFailMarket, checks success, returns JSON text response or error message.
    async ({ proposalId, amount, user }) => {
      try {
        const response = await apiClient.buyInFailMarket(proposalId, amount, user);
        
        if (!response.success) {
          return {
            content: [
              {
                type: "text" as const,
                text: response.error || 'Unknown error',
              },
            ],
            isError: true,
          };
        }
        
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify(response.data, null, 2),
            },
          ],
        };
      } catch (error: any) {
        return {
          content: [
            {
              type: "text" as const,
              text: `Error buying in fail market: ${error.message || 'Unknown error'}`,
            },
          ],
          isError: true,
        };
      }
    }
  • FutarchyApiClient helper method that proxies the buyInFailMarket action via HTTP POST to backend /proposals/{proposalId}/buy-fail endpoint.
    async buyInFailMarket(proposalId: string, amount: number, userPublicKey: string): Promise<Response> {
      try {
        const response = await fetch(`${this.baseUrl}/proposals/${proposalId}/buy-fail`, {
          method: 'POST',
          headers: {
            'Content-Type': 'application/json',
          },
          body: JSON.stringify({
            amount,
            user: userPublicKey
          })
        });
    
        if (!response.ok) {
          throw new Error(`HTTP error! Status: ${response.status}`);
        }
        const data = await response.json();
        
        return {
          success: true,
          data: data
        };
      } catch (error: any) {
        return {
          success: false,
          error: error.message || 'Failed to buy in fail market'
        };
      }
    }
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 'Buy tokens' which implies a transactional operation, but doesn't specify if this requires authentication, has rate limits, affects token balances, or what happens on failure. For a financial tool with zero annotation coverage, this is a significant gap in transparency.

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 with no wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. Every word contributes to understanding the tool's purpose.

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 complexity of a financial transaction tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'fail market' entails, the expected outcome (e.g., token transfer, price impact), or error conditions. For a tool with 3 required parameters and transactional nature, more context is needed to use it effectively.

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?

Schema description coverage is 100%, so the input schema already documents all three parameters (proposalId, amount, user) with clear descriptions. The description adds no additional meaning beyond the schema, such as explaining what 'amount' represents (e.g., token units) or how 'user' is used. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('Buy tokens') and target ('in the fail market for a proposal'), which is specific and distinguishes it from sibling tools like 'sellInFailMarket' or 'buyInPassMarket'. However, it doesn't fully explain what 'fail market' means or how it differs from 'pass market', leaving some ambiguity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'sellInFailMarket' or 'buyInPassMarket'. It doesn't mention prerequisites, such as needing a proposal in a specific state, or contextual factors like market conditions. Without this, users might struggle to choose the right tool.

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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