MCP DivulgaCandContas Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP DivulgaCandContas Serverlist candidates for mayor in São Paulo 2020"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP DivulgaCandContas Server
Um servidor MCP (Model Context Protocol) que implementa todos os serviços da API DivulgaCandContas do TSE (Tribunal Superior Eleitoral), permitindo consultas sobre candidaturas e prestação de contas eleitorais.
Funcionalidades
Este servidor implementa as seguintes ferramentas (tools) baseadas na API oficial do TSE:
🏛️ Candidaturas
listar_candidatos_municipio: Lista todos os candidatos em um município específico
consultar_candidato: Consulta informações detalhadas de um candidato
🗳️ Eleições
listar_anos_eleitorais: Lista anos eleitorais disponíveis
listar_eleicoes_ordinarias: Lista eleições ordinárias disponíveis
listar_eleicoes_suplementares: Lista eleições suplementares por estado/ano
listar_cargos_municipio: Lista cargos em disputa em um município
💰 Prestação de Contas
consultar_prestador_contas: Consulta informações de prestação de contas de candidatos
Related MCP server: Situação Eleitoral (TSE)
Instalação e Uso
Script de Gerenciamento (Recomendado)
Este projeto inclui um script de gerenciamento que facilita todas as operações:
# Tornar o script executável (apenas uma vez)
chmod +x mcp-server.sh
# Ver todas as opções disponíveis
./mcp-server.sh help
# Construir o projeto
./mcp-server.sh build
# Executar localmente
./mcp-server.sh run
# Construir e executar com Docker
./mcp-server.sh build-docker
./mcp-server.sh run-docker
# Executar testes
./mcp-server.sh test
# Ver configuração para Claude Desktop
./mcp-server.sh config
# Limpar arquivos gerados
./mcp-server.sh clean📦 Imagem Docker
A imagem Docker está disponível no Docker Hub:
🔗 Docker Hub: karnagge/mcp-divulgacandcontas
📋 Tags disponíveis:
latest- Versão mais recentev1.0.0- Versão estável 1.0.0
💾 Tamanho: ~227MB (otimizada com Alpine Linux)
🔧 Uso rápido:
docker run -it --rm karnagge/mcp-divulgacandcontas:latestVia Docker
Opção 1: Usar imagem pré-construída (Recomendado)
# Baixar e executar diretamente do Docker Hub
docker run -it --rm karnagge/mcp-divulgacandcontas:latest
# Ou executar como daemon
docker run -d --name mcp-server -p 3000:3000 karnagge/mcp-divulgacandcontas:latestOpção 2: Build local
Clone o repositório:
git clone https://github.com/karnagge/mcpcand.git cd mcpcandBuild da imagem:
docker build -t mcp-divulgacandcontas .Execute o container:
docker run -p 3000:3000 mcp-divulgacandcontas
Instalação Local
Instalar dependências:
npm install
# OU usando o script
./mcp-server.sh buildCompilar TypeScript:
npm run buildExecutar servidor:
npm start
# OU usando o script
./mcp-server.sh runModo Desenvolvimento
npm run dev
# OU usando o script para desenvolvimento contínuo
npm run watch # Em um terminal
./mcp-server.sh run # Em outro terminalConfiguração com Claude Desktop
Para usar este servidor com Claude Desktop, adicione a seguinte configuração ao seu claude_desktop_config.json:
Usando Docker
{
"mcpServers": {
"divulgacandcontas": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"mcp-divulgacandcontas-server:latest"
]
}
}
}Usando Node.js Local
{
"mcpServers": {
"divulgacandcontas": {
"command": "node",
"args": ["/caminho/absoluto/para/build/index.js"]
}
}
}Usando NPX (se publicado)
{
"mcpServers": {
"divulgacandcontas": {
"command": "npx",
"args": ["-y", "mcp-divulgacandcontas-server"]
}
}
}Uso das Ferramentas
Exemplo: Listar candidatos de São Paulo em 2020
// Parâmetros necessários
{
"ano": 2020,
"municipio": 35157, // Código de São Paulo
"eleicao": 2030402020, // Eleições municipais 2020
"cargo": 11 // Prefeito
}Exemplo: Consultar informações de um candidato
{
"ano": 2020,
"municipio": 35157,
"eleicao": 2030402020,
"candidato": 123456 // Código do candidato
}Exemplo: Listar eleições suplementares em São Paulo
{
"ano": 2020,
"uf": "SP"
}API Base
Este servidor consulta a API oficial do TSE:
Base URL:
https://divulgacandcontas.tse.jus.br/divulga/rest/v1Documentação: Swagger da API
Estrutura do Projeto
mcp-divulgacandcontas-server/
├── src/
│ └── index.ts # Servidor MCP principal
├── build/ # Código compilado (gerado)
├── Dockerfile # Configuração Docker
├── docker-compose.yml # Configuração Docker Compose
├── package.json # Dependências e scripts
├── tsconfig.json # Configuração TypeScript
└── README.md # Esta documentaçãoDesenvolvimento
Scripts Disponíveis
npm run build- Compila TypeScriptnpm run start- Executa servidor compiladonpm run dev- Compila e executa em modo desenvolvimentonpm run watch- Monitora mudanças e recompila automaticamentenpm run clean- Remove arquivos compilados
Dependências Principais
@modelcontextprotocol/sdk: SDK oficial do MCP
zod: Validação de schemas
axios: Cliente HTTP para chamadas à API do TSE
Segurança e Limitações
✅ Dados públicos oficiais do TSE
✅ Timeout configurado (30s) para requisições
✅ Validação rigorosa de parâmetros com Zod
✅ Tratamento de erros da API
⚠️ Sujeito a limitações de rate limit da API do TSE
⚠️ Dados disponíveis conforme cronograma do TSE
Códigos Úteis
Códigos de Eleição Comuns
2030402020: Eleições Municipais 20202030402024: Eleições Municipais 20242030602022: Eleições Gerais 2022
Códigos de Cargo Comuns
11: Prefeito13: Vice-prefeito51: Vereador1: Presidente3: Governador5: Senador6: Deputado Federal7: Deputado Estadual
Estados (UF)
Use a sigla de 2 letras: SP, RJ, MG, RS, etc.
Suporte
Este servidor implementa todos os endpoints documentados na API DivulgaCandContas do TSE. Para problemas ou dúvidas:
Verifique se os parâmetros estão corretos (ano, códigos de município, etc.)
Consulte a documentação oficial da API do TSE
Verifique se o serviço do TSE está disponível
Licença
MIT License - veja o arquivo LICENSE para detalhes.
Nota: Este é um projeto independente que utiliza a API pública do TSE. Não possui afiliação oficial com o Tribunal Superior Eleitoral.
Available Tools
7 toolsconsultar_candidatoC
Consulta informações detalhadas sobre um candidato específico
| Name | Required | Description | Default |
|---|---|---|---|
| ano | Yes | Ano da eleição (ex: 2020) | |
| municipio | Yes | Código do município (ex: 35157 para São Paulo) | |
| eleicao | Yes | Código da eleição (ex: 2030402020 para eleições municipais de 2020) | |
| candidato | Yes | Código do candidato |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'consulta' implies a read-only operation, the description doesn't disclose important behavioral traits such as authentication requirements, rate limits, error conditions, or what format/scope the 'informações detalhadas' includes. For a tool with 4 required parameters and no annotation coverage, this represents a significant gap in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without any unnecessary words. It's appropriately sized for a tool with a clear purpose, and every word contributes to understanding what the tool does. The structure is front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a read operation with 4 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'informações detalhadas' includes, what format the response will be in, or any behavioral constraints. For a tool that requires multiple specific identifiers to function, the description should provide more context about the nature and scope of the returned information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add any parameter semantics beyond what's already in the input schema, which has 100% description coverage. The schema already documents all 4 required parameters with descriptions and constraints. Since schema_description_coverage is high (>80%), the baseline score of 3 is appropriate even though the description provides no additional parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Consulta informações detalhadas sobre um candidato específico' (Consult detailed information about a specific candidate), which provides a specific verb ('consulta') and resource ('candidato específico'). However, it doesn't explicitly differentiate from sibling tools like 'listar_candidatos_municipio' which lists candidates rather than retrieving detailed information about one specific candidate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 when to choose this tool over sibling tools like 'listar_candidatos_municipio' for listing candidates or other tools for different types of election data. No context about prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
consultar_prestador_contasC
Consulta informações sobre prestação de contas de um candidato
| Name | Required | Description | Default |
|---|---|---|---|
| eleicao | Yes | Código da eleição | |
| ano | Yes | Ano da eleição (ex: 2020) | |
| municipio | Yes | Código do município | |
| cargo | Yes | Código do cargo | |
| candidato | Yes | Código do candidato |
TDQS
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. While 'consulta' implies a read-only operation, the description doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the information takes. For a tool with 5 required parameters and no annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the tool's purpose without unnecessary words. It's appropriately sized for a lookup tool and front-loads the essential information. Every word earns its place in conveying the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 required parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what type of financial accountability information is returned, whether results are filtered/sorted, or what happens when parameters don't match existing records. For a tool that likely returns structured financial data, more context about the response format would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all 5 parameters clearly documented in the schema (election code, year, municipality code, position code, candidate code). The description doesn't add any parameter semantics beyond what's already in the schema - it doesn't explain relationships between parameters or provide examples of valid values. The baseline score of 3 reflects adequate but minimal value addition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Consulta informações sobre prestação de contas de um candidato' (Consult information about a candidate's financial accountability), which is a specific verb+resource combination. It distinguishes from siblings like 'consultar_candidato' (general candidate info) by focusing specifically on financial accountability information. However, it doesn't explicitly contrast with other siblings that might also provide financial data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 prerequisites, context requirements, or comparison to sibling tools like 'consultar_candidato' (which might provide overlapping or complementary information). The agent must infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listar_anos_eleitoraisB
Lista todos os anos eleitorais disponíveis no sistema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose any behavioral traits such as rate limits, authentication needs, or what 'disponíveis' entails (e.g., cached data, real-time). For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is adequate as a basic list operation. However, with no annotations and no output schema, it lacks details on return format (e.g., list structure, data types) and behavioral context, which could be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 for this dimension.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lista') and resource ('anos eleitorais disponíveis no sistema'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'listar_eleicoes_ordinarias' or 'listar_eleicoes_suplementares', which appear to list specific types of elections rather than years.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context for usage, or how it relates to sibling tools that list elections or candidates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listar_candidatos_municipioB
Lista todos os candidatos para eleições em um município específico
| Name | Required | Description | Default |
|---|---|---|---|
| ano | Yes | Ano da eleição (ex: 2020) | |
| municipio | Yes | Código do município (ex: 35157 para São Paulo) | |
| eleicao | Yes | Código da eleição (ex: 2030402020 para eleições municipais de 2020) | |
| cargo | Yes | Código do cargo |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't mention potential limitations like pagination, rate limits, authentication needs, or what happens with invalid inputs. For a tool with 4 required parameters and no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It directly communicates what the tool does in a compact form, earning full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 required parameters, no output schema, no annotations), the description is minimally adequate. It clarifies the scope (municipality-specific candidates) but omits details on return format, error handling, or sibling tool relationships, leaving room for improvement in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter well-documented in the schema (e.g., 'ano' as election year with examples). The description adds no additional parameter semantics beyond implying filtering by municipality and election context, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lista') and resource ('todos os candidatos') with specific context ('para eleições em um município específico'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'consultar_candidato' or 'listar_cargos_municipio', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'consultar_candidato' (which might fetch individual candidate details) or other list tools. It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listar_cargos_municipioC
Lista os cargos em disputa em um município específico
| Name | Required | Description | Default |
|---|---|---|---|
| eleicao | Yes | Código da eleição | |
| municipio | Yes | Código do município |
TDQS
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. While 'Lista' implies a read-only operation, it doesn't specify whether this is a safe query, what permissions are needed, if there are rate limits, or the format/scope of the returned data. For a tool with zero annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 without unnecessary words. It is appropriately sized for a simple listing tool and front-loads the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 'cargos em disputa' entails (e.g., types of positions, data returned), behavioral traits like safety or limitations, or how results are structured, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters ('eleicao' and 'municipio') documented as numeric codes. The description adds no additional semantic context beyond what the schema provides, such as example values or format details, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lista' - lists) and the resource ('cargos em disputa' - positions in dispute) with a specific scope ('em um município específico' - in a specific municipality). It distinguishes itself from siblings like 'listar_candidatos_municipio' by focusing on positions rather than candidates, though it doesn't explicitly mention this distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'listar_candidatos_municipio' or 'consultar_candidato'. It mentions the municipality scope but doesn't specify prerequisites, exclusions, or complementary tools, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listar_eleicoes_ordinariasB
Lista todas as eleições ordinárias disponíveis para consulta
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool lists elections for consultation, implying a read-only operation, but doesn't disclose behavioral traits such as pagination, rate limits, authentication needs, or what 'disponíveis para consulta' entails (e.g., availability constraints). The description is minimal and lacks critical operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for its simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple tool with zero parameters, the description is incomplete. It lacks details on return values (e.g., format, fields), behavioral aspects like error handling or data freshness, and doesn't leverage the opportunity to clarify usage relative to siblings. For a list operation, more context on output and constraints is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. Baseline is 4 for zero parameters, as the description doesn't need to compensate for any schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lista todas') and resource ('eleições ordinárias'), making the purpose understandable. It distinguishes from siblings like 'listar_eleicoes_suplementares' by specifying 'ordinárias' but doesn't explicitly contrast them. The description is specific but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'listar_anos_eleitorais' or 'listar_eleicoes_suplementares'. The description implies usage for listing ordinary elections but offers no context on prerequisites, exclusions, or comparative scenarios with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listar_eleicoes_suplementaresC
Lista eleições suplementares em um estado e ano específicos
| Name | Required | Description | Default |
|---|---|---|---|
| ano | Yes | Ano da eleição (ex: 2020) | |
| uf | Yes | Sigla da unidade federativa (ex: SP, RJ) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes a read operation ('Lista') but doesn't disclose behavioral traits like whether it returns all results or is paginated, what format the output takes, error conditions, or any rate limits. The description is minimal and 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.
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 without any fluff. It is appropriately sized and front-loaded, with every word contributing to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with two required parameters. It lacks information on output format, error handling, or behavioral details, leaving significant gaps for an AI agent to understand how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('ano' and 'uf') well-documented in the schema. The description mentions these parameters ('estado e ano específicos') but adds no meaning beyond what the schema already provides, such as explaining why these filters are necessary or their impact on results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lista' - lists) and resource ('eleições suplementares' - supplementary elections) with specific filtering criteria ('em um estado e ano específicos' - in a specific state and year). It distinguishes from obvious siblings like 'listar_eleicoes_ordinarias' by specifying 'suplementares' vs 'ordinarias', though it doesn't explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'listar_eleicoes_ordinarias' or 'listar_anos_eleitorais'. It states what it does but offers no context about appropriate use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
4 tool updates
v1.0.0- Changed
consultar_candidato1 field changed- changed
Input schema / properties / ano / maximumPrevious value: -2025New value: +2026
- Changed
consultar_prestador_contas1 field changed- changed
Input schema / properties / ano / maximumPrevious value: -2025New value: +2026
- Changed
listar_candidatos_municipio1 field changed- changed
Input schema / properties / ano / maximumPrevious value: -2025New value: +2026
- Changed
listar_eleicoes_suplementares1 field changed- changed
Input schema / properties / ano / maximumPrevious value: -2025New value: +2026
7 tool updates
- First observed
consultar_candidato - First observed
consultar_prestador_contas - First observed
listar_anos_eleitorais - First observed
listar_candidatos_municipio - First observed
listar_cargos_municipio - First observed
listar_eleicoes_ordinarias - First observed
listar_eleicoes_suplementares
TDQS
Every tool has a clearly distinct purpose with no overlap. The tools target different resources (candidates, accounts, years, municipalities, positions, elections) and actions (consult, list), making misselection unlikely. For example, consultar_candidato retrieves detailed candidate info while listar_candidatos_municipio lists candidates by municipality.
Tool names follow a perfectly consistent verb_noun pattern in Portuguese (consultar_X, listar_X). All tools use snake_case uniformly, with clear verb choices (consultar for detailed queries, listar for enumerations). This predictability helps agents understand tool purposes at a glance.
Seven tools is well-scoped for an electoral data server, covering core queries without bloat. Each tool earns its place by addressing distinct aspects like candidates, accounts, years, municipalities, positions, and election types. This count allows comprehensive coverage while remaining manageable.
The toolset provides strong coverage for querying electoral data, with tools for candidates, accounts, years, municipalities, positions, and elections. A minor gap exists in update/delete operations, but this is reasonable for a read-only public data server. Agents can retrieve comprehensive information without dead ends.
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Looks up a person's voter ID and polling place at the Electoral Court (TSE) from the name, CPF, vote
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