Discovering MCP Tools
Nexus is fully MCP-compatible, which means your AI agents can be equipped with thousands of tools from the Smithery.ai ecosystem and beyond. This includes tools for APIs, data processing, visualization, scraping, automation, and much more.
To build powerful agents, you first need to discover which tools are available, explore what they do, and understand how to configure them.
Get Built-in Nexus Tools
GET /mcp/client/nexus
This returns a list of tools that come bundled with Nexus by default. These require no external setup and are ready to use.
Response example:
{
"status": "ok",
"data": {
"tools": [
{
"tool_name": "find_metadata",
"description": "Searches column-level metadata across all connected data sources.",
"tool_server_id": "nexus",
"config": {}
},
{
"tool_name": "execute_sql",
"description": "Executes Nexus SQL queries across structured datasets, databases and API endpoints.",
"tool_server_id": "nexus",
"config": {}
},
{
"tool_name": "create_graph",
"description": "Generates and returns charts from tabular result data using matplotlib.",
"tool_server_id": "nexus",
"config": {}
}
]
}
}
These tools form the backbone of most query + visualization workflows in Nexus.
Search MCP Tool Servers
GET /mcp/client/search?q={query}&page={page}
Use this to search the global MCP ecosystem for servers offering tools related to your query. This is the best way to find capabilities beyond what's bundled in Nexus.
q— a text search query (e.g.,"weather","salesforce","image").page— optional; defaults to 1.
Example request:
GET /mcp/client/search?q=image
Response example:
{
"status": "ok",
"data": {
"servers": [
{
"qualifiedName": "@PawNzZi/image-server",
"displayName": "text2image",
"description": "Transform text prompts into stunning images effortlessly…",
"createdAt": "2025-04-08T04:04:08.356Z",
"useCount": 120,
"homepage": "https://smithery.ai/server/@PawNzZi/image-server"
}
]
}
}
Get MCP Server Details
GET /mcp/client/server?q={qualified_name}
After finding a promising server via search, use this endpoint to get its full details, including:
- The tools it provides
- Input schemas and config options
- Deployment URLs
- Security scan status
Example request:
GET /mcp/client/server?q=@PawNzZi/image-server
Response example:
{
"status": "ok",
"data": {
"server": {
"qualifiedName": "@PawNzZi/image-server",
"displayName": "text2image",
"remote": true,
"iconUrl": "https://icons.duckduckgo.com/ip3/github.com.ico",
"connections": [
{
"type": "http",
"deploymentUrl": "https://server.smithery.ai/@PawNzZi/image-server/mcp",
"configSchema": {}
}
],
"security": {
"scanPassed": true
},
"tools": [
{
"name": "image_generation",
"description": "Image generation assistant, please imagine and describe a complete picture…",
"inputSchema": {
"type": "object",
"required": ["image_prompt"],
"properties": {
"width": { "type": "integer", "default": 1024 },
"height": { "type": "integer", "default": 1024 },
"image_prompt": { "type": "string" }
}
}
}
]
}
}
}
How to Use This Data
Once you've identified a tool you want to use:
-
Get its qualified name (e.g.,
@PawNzZi/image-server) -
Get server details to retrieve its
deploymentUrl, config schema, and list of tools. -
Add the tool to your agent via the
POST /agentendpoint by specifying:tool_nametool_server_id(the qualified name)- Any required
propertiesbased on its input or config schema
Read more about how to configure agent and agent tools here.
Tools that require user-provided config (like API keys, usernames, or prompts) will list those in the
propertiesfield or input schema.