Skip to main content
Glama
0xKoller

MCP Argentina Datos

by 0xKoller

senado-actas

Access official Senate session records from Argentina to research legislative proceedings and track parliamentary activities.

Instructions

Devuelve las actas del senado

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.ts:397-421 (handler)
    The MCP tool handler for 'senado-actas' that invokes getSenadoActas(), processes the response, handles empty results and errors, and formats as JSON content.
    server.tool("senado-actas", "Devuelve las actas del senado", {}, async ({}) => {
      try {
        const data = await getSenadoActas();
        if (data.length === 0) {
          return {
            content: [{ type: "text", text: "No se encontraron actas" }],
          };
        }
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(data, null, 2),
              mimeType: "application/json",
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            { type: "text", text: "Error al obtener las actas del senado" },
          ],
        };
      }
    });
  • main.ts:69-73 (schema)
    Schema definition for the 'senado-actas' tool in the server constructor, specifying name, description, and empty parameters.
    {
      name: "senado-actas",
      description: "Devuelve las actas del senado",
      parameters: {},
    },
  • Helper function that performs the actual API fetch for senate actas from 'https://api.argentinadatos.com/v1/senado/actas'.
    export const getSenadoActas = async () => {
      const actas = await fetch(`${BASE_URL}/senado/actas`);
      const data = await actas.json();
      return data;
    };
  • main.ts:397-421 (registration)
    Registration of the 'senado-actas' tool using server.tool, including schema inline and handler.
    server.tool("senado-actas", "Devuelve las actas del senado", {}, async ({}) => {
      try {
        const data = await getSenadoActas();
        if (data.length === 0) {
          return {
            content: [{ type: "text", text: "No se encontraron actas" }],
          };
        }
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(data, null, 2),
              mimeType: "application/json",
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            { type: "text", text: "Error al obtener las actas del senado" },
          ],
        };
      }
    });
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 states the tool returns senate minutes but doesn't describe any behavioral traits, such as whether it's read-only, if it requires authentication, rate limits, or what format the data is in. This is a significant gap for a tool with no annotation coverage.

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, clear sentence: 'Devuelve las actas del senado.' It is front-loaded with the core purpose, has no unnecessary words, and efficiently conveys the tool's function without any waste.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values are (e.g., format, structure, or content of the actas), which is crucial for an agent to understand the tool's output. This leaves gaps in understanding how to use the tool effectively.

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, and the schema description coverage is 100%, meaning there are no parameters to document. The description doesn't need to add parameter semantics, so it meets the baseline expectation. No additional value is required here.

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 'Devuelve las actas del senado' clearly states the tool's purpose: it returns the minutes/records of the senate. It uses a specific verb ('devuelve') and resource ('actas del senado'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'senado-actas-por-anio', which suggests a similar function with year filtering, so it misses full sibling distinction.

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. It doesn't mention any context, prerequisites, or exclusions, such as how it differs from 'senado-actas-por-anio' (which likely filters by year). This lack of comparative information leaves the agent without clear usage instructions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/0xKoller/mcp-argentina-datos'

If you have feedback or need assistance with the MCP directory API, please join our Discord server