Un servidor MCP para administrar y navegar por los repositorios de canalización de nf-core.
Lista de repositorios locales de nf-core (rnaseq, sarek, módulos, herramientas)
Acceda a configuraciones de canalización y flujos de trabajo
Buscar en archivos de canalización
Explorar los módulos de canalización
Related MCP server: pipen-mcp
cd nf-core_mcp
npm install
# Build TypeScript
npm run build
# Start the server
npm start# Build the Docker image
cd nf-core_mcp
docker build -t nf-core-mcp .
# Run the container
docker run -i --rm \
-v "/path/to/your/workspace:/app/workspace" \
nf-core-mcpPara agregar nuevos repositorios de canalización de nf-core al espacio de trabajo:
Clonar los repositorios :
# Navigate to your workspace directory (example for Windows)
cd /path/to/your/workspace
# Clone desired nf-core repositories
git clone https://github.com/nf-core/rnaseq.git
git clone https://github.com/nf-core/sarek.git
git clone https://github.com/nf-core/modules.git
# Add any other nf-core pipeline you want to manageEstructura del directorio : Su espacio de trabajo debería verse así:
workspace/
├── rnaseq/
├── sarek/
├── modules/
└── your-new-pipeline/Verificar la instalación : después de iniciar el servidor MCP, utilice el comando list-pipelines para verificar que se detecten sus nuevas canalizaciones:
list-pipelinesNota: El servidor MCP detectará y administrará automáticamente cualquier repositorio de canalización nf-core en su directorio de espacio de trabajo.
list-pipelines
Enumera todas las canalizaciones de nf-core en el espacio de trabajo
Muestra el estado del archivo de configuración
No se requieren parámetros
get-pipeline-modules
Obtiene información del módulo desde una canalización
Parámetros:
pipeline : nombre de la tubería (rnaseq, sarek o módulos)
search-pipelines
Búsquedas a través de archivos de canalización
Parámetros:
query : Consulta de búsqueda
pipeline (opcional): pipeline específico para buscar
pipeline-config
Obtiene la configuración de la tubería
Formato de URI: pipeline://{name}/config
Parámetros:
name : nombre de la tubería (rnaseq, sarek o módulos)
pipeline-workflow
Obtiene el flujo de trabajo de la canalización
Formato de URI: pipeline://{name}/workflow
Parámetros:
name : nombre de la tubería (rnaseq, sarek o módulos)
Agregue lo siguiente a su mcp.json :
{
"mcpServers": {
"nf-core": {
"command": "npx",
"args": ["-y", "nf-core-mcp"]
}
}
}Agregue lo siguiente a su mcp.json :
{
"mcpServers": {
"nf-core": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-v",
"/path/to/your/workspace:/app/workspace",
"nf-core-mcp"
]
}
}
}Usando el servidor MCP en Cursor:
# List available pipelines
list-pipelines
# Get modules from rnaseq pipeline
get-pipeline-modules pipeline=rnaseq
# Search in all pipelines
search-pipelines query="fastqc"
# Search in specific pipeline
search-pipelines query="fastqc" pipeline=rnaseq
# Access pipeline configuration
pipeline://rnaseq/config
# Access workflow
pipeline://rnaseq/workflow# If installed globally
nf-core-mcp
# If installed locally
npx nf-core-mcp
# Using npx without installation
npx -y nf-core-mcpdocker run -it --rm \
-v /path/to/your/workspace:/app/workspace \
nf-core-mcp# Install dependencies
npm install
# Build TypeScript
npm run build
# Run in development mode
npm run dev
# Run tests
npm test
# Run linter
npm run lintInstituto Tecnológico de Massachusetts (MIT)
| Name | Required | Description | Default |
|---|---|---|---|
| pipeline | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| pipeline | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0get-pipeline-moduleslist-pipelinessearch-pipelinesScored across 3 tools
The three tools have clearly distinct purposes: get-pipeline-modules retrieves modules for a specific pipeline, list-pipelines enumerates available pipelines, and search-pipelines finds pipelines based on criteria. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent verb-noun pattern with hyphens (e.g., get-pipeline-modules, list-pipelines, search-pipelines). The naming is uniform and predictable, using clear action verbs paired with relevant nouns.
With only three tools, the server feels thin for a pipeline management domain, potentially lacking operations like create, update, or delete pipelines. However, the tools cover basic discovery and inspection, which might be sufficient for a limited scope.
The toolset is severely incomplete for pipeline management, missing essential CRUD operations such as creating, updating, or deleting pipelines. It only supports discovery and inspection, leaving significant gaps that could hinder agent workflows.
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