# Finnish Foreign Trade (Tulli) MCP (`nectia/finnish-foreign-trade-mcp`) Actor Search Finnish Customs (Tulli) foreign-trade tables, inspect their dimensions, and query clean flattened import/export data by commodity, country and period. - **URL**: https://apify.com/nectia/finnish-foreign-trade-mcp.md - **Developed by:** [Anton Aouat](https://apify.com/nectia) (community) - **Categories:** MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 search trade tables This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Finnish Foreign Trade (Tulli) MCP An MCP server that gives an AI agent clean access to **Finnish Customs (Tulli) foreign-trade statistics** — imports and exports by commodity, country, and period. It decodes Tulli's "Uljas" **json-stat** trade cubes into flat, labelled rows an agent can read directly. Data © Finnish Customs, Uljas statistical database, licensed **CC BY 4.0**. ### Tools | Tool | What it does | |------|--------------| | `search_trade_tables` | List trade tables (CN goods, SITC, NACE industry, BEC), filter by keyword. Returns each table's `ifile`. | | `get_trade_dimensions` | A table's dimensions + classification granularities (CN2…CN8, Year/Quarter/Month, Country/Continents). Pass a `classification` to also get its value codes. | | `get_trade_data` | Query flattened import/export rows (json-stat decoded), by commodity × country × period × flow × indicator. | Agents chain them: **search table → dimensions (learn codes) → data**. ### Example > "Finland's monthly total imports over the last year?" 1. `search_trade_tables({ query: "CN" })` → `ifile` for `ULJAS_CN`. 2. `get_trade_dimensions({ ifile, classification: "Flow" })` → Flow codes (1=imports, 2=exports), dimensions. 3. `get_trade_data({ ifile, selections: [ { classification: "Classification of Products CN2", code: "00 - 99" }, { classification: "Time period", anchor: "FIRST", count: 12 }, { classification: "Country", code: "AA" }, { classification: "Flow", code: "1" }, { classification: "Indicators", code: "V1" } ] })` → 12 monthly import totals in EUR. ### Notes on this API (hard-won) - The Uljas API responses are **BOM-prefixed** and the selection grammar needs `= * ;` sent **literally** — Node's `fetch`/undici mangles it (500s), so the client uses the raw `https` module. All handled internally. - **Selection grammar:** each dimension takes a single `code`, or a relative range via `anchor` (`FIRST`/`LAST`) + `count`. For `Time period`, `FIRST` = the most recent periods. - Current-year detail may be incomplete (product-level nulls); aggregates (`00 - 99`, all countries `AA`) are published first. Limit: 50,000 cells/query (guarded client-side). ### Local use (stdio) ```bash npm install && npm run build ```` ```json { "mcpServers": { "tulli": { "command": "node", "args": ["/abs/path/servers/tulli-trade/dist/server.js"] } } } ``` No API key — Tulli/Uljas is open data. ### Development ```bash npm run typecheck # tsc --noEmit npm test # vitest — unit tests vs recorded real fixtures (offline) npm run smoke # live: boots the server, real MCP handshake + real Uljas calls npm run build # produces dist/ ``` Windows: run tools directly (`node ./node_modules/vitest/vitest.mjs run`) or via PowerShell. ### Design - `src/tulli/client.ts` — HTTP only (Stats/Dims/Class/Data via the raw `https` module). Custom minimal URL encoder, BOM strip, throttle + cache, typed `TulliApiError`. - `src/tulli/normalize.ts` — the moat: flatten **json-stat v1** cubes → flat rows; tidy stats/dims. - `src/tulli/query.ts` — build the Data selection grammar + guard the 50k-cell cap. - `src/tools.ts` — the 3 MCP tools + Pay-Per-Event billing hook. - `src/server.ts` (stdio) / `src/standby.ts` (Apify HTTP) — both call one factory. # Actor input Schema ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nectia/finnish-foreign-trade-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nectia/finnish-foreign-trade-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call nectia/finnish-foreign-trade-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nectia/finnish-foreign-trade-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Finnish Foreign Trade (Tulli) MCP", "description": "Search Finnish Customs (Tulli) foreign-trade tables, inspect their dimensions, and query clean flattened import/export data by commodity, country and period.", "version": "0.1", "x-build-id": "pGhvrxUIxGLbRDY5h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nectia~finnish-foreign-trade-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nectia-finnish-foreign-trade-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nectia~finnish-foreign-trade-mcp/runs": { "post": { "operationId": "runs-sync-nectia-finnish-foreign-trade-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nectia~finnish-foreign-trade-mcp/run-sync": { "post": { "operationId": "run-sync-nectia-finnish-foreign-trade-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": {} }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```