Pluggy MCP Starter
Click on "Deploy 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., "@Pluggy MCP Starterhow much did I spend on Uber this month?"
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.
Pluggy MCP Starter
Pergunte à sua IA quanto gastou, onde gastou e quais contas estão conectadas. Este MCP lê as contas e transações da sua aplicação Pluggy. Ele não move dinheiro nem altera dados.
Exemplos de perguntas que ele responde:
"Quanto gastei com Uber neste mês?"
"Mostre meus gastos por categoria nos últimos 90 dias."
"Quais contas e cartões eu conectei?"
Qual caminho faz sentido?
Situação | Use |
Você quer as ferramentas genéricas mantidas pela Pluggy | |
Você quer fazer perguntas financeiras sobre mais de um banco | Este projeto. Ele junta os dados de vários |
Você usa Codex, Claude Code, Cursor ou Claude Desktop no seu computador | A instalação local com |
Você usa ChatGPT web ou Claude.ai | Um servidor HTTP com HTTPS, ou o Secure MCP Tunnel da OpenAI. |
Um cliente na nuvem não consegue abrir um processo no seu computador. Por isso, ChatGPT web e Claude.ai precisam de uma opção remota.
Related MCP server: bank-mcp
Antes de instalar
Conecte cada banco e cartão que quer consultar. Cada conexão cria um itemId. Guarde todos eles:
PLUGGY_ITEM_IDS=item-id-santander,item-id-nubank,item-id-itauSe você informar um único ID, verá somente as contas daquele banco. Este foi o motivo de o projeto original mostrar apenas uma conexão.
O guia do Meu Pluggy mostra como criar e guardar as conexões. A API do Pluggy não lista os Items existentes. Você precisa registrar o ID quando concluir cada conexão. Veja também a documentação de Items e Accounts.
Instalação local
Adicione isto à configuração MCP do seu cliente:
{
"mcpServers": {
"pluggy": {
"command": "npx",
"args": ["-y", "github:caiomioto2/pluggy-mcp-starter"],
"env": {
"PLUGGY_CLIENT_ID": "seu-client-id",
"PLUGGY_CLIENT_SECRET": "seu-client-secret",
"PLUGGY_ITEM_IDS": "item-id-1,item-id-2"
}
}
}
}No Claude Code:
claude mcp add pluggy \
--env PLUGGY_CLIENT_ID=seu-client-id \
--env PLUGGY_CLIENT_SECRET=seu-client-secret \
--env PLUGGY_ITEM_IDS=item-id-1,item-id-2 \
-- npx -y github:caiomioto2/pluggy-mcp-starterHoje o npx baixa o projeto do GitHub. Quando o pacote estiver publicado no npm, troque o argumento por @caiomioto/pluggy-mcp.
Uso no ChatGPT web ou Claude.ai
Servidor HTTP próprio
git clone https://github.com/caiomioto2/pluggy-mcp-starter.git
cd pluggy-mcp-starter
cp .env.example .env
docker compose up -d --buildPreencha o .env com suas credenciais Pluggy, todos os itemIds e um MCP_HTTP_TOKEN longo. O MCP atende em http://SEU_SERVIDOR:3000/mcp. Coloque um proxy HTTPS na frente dele antes de registrá-lo em um cliente na nuvem.
Secure MCP Tunnel da OpenAI
O tunnel conecta um MCP privado a produtos OpenAI compatíveis sem abrir uma URL pública. O guia de tunnel inclui o docker compose e o registro no ChatGPT.
Ele não transforma o projeto em plugin público. Para distribuir um plugin, hospede o MCP em uma URL HTTPS estável. A documentação da OpenAI explica a diferença.
Ferramentas
pluggy_schema mostra as tabelas disponíveis e exemplos de SQL.
pluggy_query executa apenas consultas SELECT nas tabelas accounts e transactions.
Cada linha de accounts também informa a origem Pluggy: item_id, connector_id, connector_name e, quando a API disponibiliza, institution_name. Contas e cartões da mesma conexão compartilham o mesmo item_id. O projeto não tenta deduzir a instituição por descrição de transação; se a Pluggy não enviar o nome da instituição, o campo vem como NULL.
SELECT merchant_name, description, amount, date, account_name
FROM transactions
WHERE date >= '2026-01-01'
ORDER BY date DESC
LIMIT 50O servidor bloqueia comandos que escrevem ou alteram o banco de consulta.
Segurança
Não coloque clientSecret, itemId, extrato ou token em commit, issue ou chat público. Use .env no computador, secrets do seu deploy ou um cofre de segredos. Este repositório tem somente valores de exemplo.
Desenvolvimento
npm install
npm test
npm run buildLicença
MIT.
Available Tools
2 toolspluggy_queryQuery Pluggy accounts and transactions with SQLARead-onlyIdempotent
Read-only SQLite SELECT over accounts and transactions for the requested UTC period. accounts includes every account returned by every configured Pluggy connection, including accounts without transactions. Reuses collection in memory for 15 minutes and returns coverage metadata. Call pluggy_schema before computing totals.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| sql | Yes | ||
| from | Yes | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavior beyond that: a 15-minute in-memory collection cache, returned coverage metadata, and the fact that accounts include connections with zero transactions — a non-obvious data-shape caveat.
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?
Four short sentences, front-loaded with the operation and scope, with no redundant restatement of the name or title. The prerequisite call is placed last, where an agent will read it before invoking.
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?
No output schema exists, and the description partially compensates by mentioning coverage metadata and the accounts-without-transactions case. It is nearly complete for a 4-parameter read tool, but the absence of date-format and limit guidance leaves a small gap.
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 0%, so the description must carry the parameter burden. It clarifies that sql is a SELECT-only SQLite query and that from/to delimit a UTC period, but gives no date format and never mentions the limit parameter or its 200-row cap, leaving meaningful 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?
States a specific verb and dialect (read-only SQLite SELECT) over named resources (accounts and transactions) scoped to a UTC period. It also distinguishes itself from the sibling by naming pluggy_schema as a prerequisite rather than an alternative query path.
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?
Gives explicit sequencing guidance ("Call pluggy_schema before computing totals") and implies the tool's role is querying for aggregates over a period. It does not, however, state when NOT to use it or contrast it with a filtering alternative, since pluggy_schema is the only sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pluggy_schemaPluggy finance schemaBRead-onlyIdempotent
SQL fields, semantics, and transaction limitations. Does not access secrets.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive, and open-world behavior. The description adds a useful security note ('Does not access secrets'), but it does not disclose return format, scope of schema coverage, or other behavioral context beyond the annotations.
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 very short and front-loads the key content categories. Every sentence is brief, though the extreme terseness leaves some ambiguity that a slightly fuller structure could resolve.
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?
For a zero-parameter, read-only metadata tool with rich annotations and no output schema, the description covers the broad content areas and a security caveat. However, it does not clarify the relationship to pluggy_query or exactly what the schema output contains, leaving an agent to infer key context.
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 takes zero parameters, so there is no parameter semantics burden. Per the rubric, a zero-parameter tool receives a baseline of 4 regardless of description detail.
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 lists content categories (SQL fields, semantics, transaction limitations) but does not state a clear action such as returning or describing a schema. The name and title imply it is a schema tool, but the description itself is vague about what it does. It also does not distinguish this tool from the sibling pluggy_query.
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?
There is no explicit guidance on when to use this tool versus pluggy_query or any other alternative. The phrase 'transaction limitations' weakly implies it should be consulted before querying, but no condition or alternative is stated.
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.
2 tool updates
v0.1.0- First observed
pluggy_query - First observed
pluggy_schema
TDQS
Scored across 2 tools
The two tools have clearly distinct roles: pluggy_schema provides metadata and semantics, while pluggy_query executes read-only SQL. The query description explicitly directs agents to call the schema tool first, reducing any risk of misselection.
Both tools follow the same pluggy_ prefix and snake_case convention. The names are predictable and readable.
Only two tools are provided, which is borderline thin for a server with a defined domain. While the starter scope makes this acceptable, it is below the typical well-scoped range of 3-15 tools.
For a read-only query server, schema discovery plus SQL SELECT covers the core lifecycle. Minor convenience gaps exist, such as direct connection/account listing, but raw SQL can work around them.
Maintenance
Related MCP Connectors
Read-only bank & investment accounts via Plaid: balances, holdings, transactions, SQL analytics.
Chat with your bank data: balances, transactions, budgets, bills. Reads only, never moves money.
Ask data questions in natural language. Get SQL, insights, and charts from your databases.
Read-only access to your bank, investment, and crypto accounts: balances, transactions, holdings.
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