eRegulations MCP Server
The eRegulations MCP Server provides structured, AI-friendly access to administrative procedures data via the Model Context Protocol (MCP).
You can:
List all available procedures in the eRegulations system
Get detailed information about a specific procedure by its ID
Retrieve information about specific steps within a procedure
Search for procedures using keywords
Utilize predefined prompt templates that guide AI models in correctly using the server's tools
Enables deployment of the MCP server using Docker Compose for containerized setup and management.
Supports version control for cloning and managing the eRegulations MCP server codebase.
Provides integration for cloning the eRegulations MCP server repository from GitHub.
Facilitates installation of dependencies and project building through npm package management.
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., "@eRegulations MCP Server what are the steps to register a business in Tanzania?"
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.
eRegulations MCP Server
A Model Context Protocol (MCP) server implementation for accessing eRegulations API data. This server provides structured, AI-friendly access to eRegulations instances, making it easier for AI models to answer user questions about administrative procedures.
Features
Access eRegulations data through a standardized protocol
Query procedures, steps, requirements, and costs
MCP prompt templates to guide LLM tool usage
Streamlined implementation using standard I/O connections
Related MCP server: MCP Boilerplate
Usage
Running with Docker (Recommended)
The recommended way to run the server is using the published Docker image from the GitHub Container Registry (GHCR). This ensures a consistent and isolated environment.
# Pull the latest image (optional)
docker pull ghcr.io/unctad-ai/eregulations-mcp-server:latest
# Run the server, providing the target eRegulations API URL
export EREGULATIONS_API_URL="https://your-eregulations-api.com"
docker run -i --rm -e EREGULATIONS_API_URL ghcr.io/unctad-ai/eregulations-mcp-serverReplace https://your-eregulations-api.com with the actual base URL of the eRegulations instance you want to connect to (e.g., https://api-tanzania.tradeportal.org).
The server listens for MCP JSON requests on standard input and sends responses to standard output.
Example Client Configuration
Here's an example of how a client (like Claude) might be configured to use this server via Docker:
{
"mcpServers": {
"eregulations": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"EREGULATIONS_API_URL",
"ghcr.io/unctad-ai/eregulations-mcp-server:latest"
],
"env": {
"EREGULATIONS_API_URL": "https://your-eregulations-api.com"
}
}
}
}(Remember to replace the EREGULATIONS_API_URL value in the env section as well.)
Installation via Smithery
Alternatively, you can install and run the server using Smithery:
Visit https://smithery.ai/server/@unctad-ai/eregulations-mcp-server for the installation command.
Installation via npm Registry (Deprecated)
Running the server directly using npx is deprecated due to potential environment inconsistencies.
~~```bash
Deprecated: Set environment variables and run with npx
export EREGULATIONS_API_URL=https://example.com/api && export NODE_ENV=production && npx -y @unctad-ai/eregulations-mcp-server@latest
## Configuration
The server requires the URL of the target eRegulations API.
### Environment Variables
- `EREGULATIONS_API_URL`: **(Required)** URL of the eRegulations API to connect to (e.g., `https://api-tanzania.tradeportal.org`). Passed to the Docker container using the `-e` flag.
## Available Tools
The MCP server provides the following tools:
### `listProcedures`
Lists all available procedures in the eRegulations system.
### `getProcedureDetails`
Gets detailed information about a specific procedure by its ID.
Parameters:
- `procedureId`: ID of the procedure to retrieve
### `getProcedureStep`
Gets information about a specific step within a procedure.
Parameters:
- `procedureId`: ID of the procedure
- `stepId`: ID of the step within the procedure
### `searchProcedures`
Searches for procedures by keyword or phrase. Note: This currently searches related objectives based on the underlying API and may include results beyond direct procedure names.
Parameters:
- `keyword`: The keyword or phrase to search for
## Prompt Templates
The server provides prompt templates to guide LLMs in using the available tools correctly. These templates explain the proper format and parameters for each tool. LLM clients that support the MCP prompt templates capability will automatically receive these templates to improve their ability to work with the API.
## Development
```bash
# Run in development mode
npm run start
# Run tests
npm test
# Run tests with watch mode
npm run test:watch
# Run test client
npm run test-client
```Available Tools
4 toolsgetProcedureDetailsD
Inputs: procedureId (required).
getProcedureStepD
Inputs: procedureId (required), stepId (required).
listProceduresD
Inputs: no named parameters.
searchProceduresD
Inputs: keyword (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
The tools have overlapping purposes focused on procedures, but their names suggest distinct functions: getProcedureDetails likely retrieves comprehensive information, getProcedureStep targets specific steps, listProcedures enumerates procedures, and searchProcedures finds them based on criteria. Without descriptions, some ambiguity remains about the exact boundaries between getProcedureDetails and getProcedureStep, but the naming provides reasonable differentiation.
All tool names follow a consistent verb_noun pattern with camelCase styling: getProcedureDetails, getProcedureStep, listProcedures, and searchProcedures. The verbs (get, list, search) are clear and appropriate, and the noun 'Procedures' is consistently used, making the naming highly predictable and readable.
With 4 tools, the count is reasonable for a server focused on regulations or procedures, as it covers key operations like listing, searching, and retrieving details. It might be slightly thin if more complex actions (e.g., create, update, delete) are needed for the domain, but for a read-only or query-focused interface, it is well-scoped and manageable.
The tool set provides good read/search coverage for procedures, including listing, searching, and getting details/steps, which suggests a query-oriented domain. However, there are notable gaps: no create, update, or delete tools imply a read-only surface, which might be intentional but limits agent workflows if modifications are needed. Without descriptions, it's unclear if this is by design or an omission.
Related MCP Connectors
A Model Context Protocol server for Wix AI tools
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
KVK Handelsregister AI Connect: hosted MCP server for the Dutch business register.
Model Context Protocol server for Studex tools, notifications, and profile integrations
Related MCP Servers
- AlicenseBqualityDmaintenanceAn implementation of the Model Context Protocol server that enables AI models to communicate with Edge Security Acceleration (ESA) services, allowing models to manage routines, deployments, routes, records, and sites through standardized protocols.4269 npm27MIT
- AlicenseNot gradedqualityDmaintenanceA server that implements the Model Context Protocol, providing a standardized way to connect AI models to different data sources and tools.12 npm12MIT
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol server that provides AI models with structured access to external data and services, acting as a bridge between AI assistants and applications, databases, and APIs in a standardized, secure way.2-
- AlicenseCqualityDmaintenanceA collection of Model Context Protocol servers providing advanced capabilities for AI assistants including professional accuracy enforcement, tool safety protocols, user preference management, and intelligent context monitoring.5MIT