File size: 4,885 Bytes
cec8267
 
 
 
b7c3fee
cec8267
 
 
 
 
 
 
b7c3fee
 
 
 
 
 
 
 
1f9050d
 
b7c3fee
 
 
 
 
 
1f9050d
 
cec8267
1f9050d
b7c3fee
1f9050d
 
 
 
b7c3fee
 
 
 
 
1f9050d
b7c3fee
1f9050d
 
cec8267
b7c3fee
 
 
cec8267
 
 
b7c3fee
 
 
 
 
cec8267
b7c3fee
cec8267
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b7c3fee
 
 
1f9050d
b7c3fee
 
1f9050d
 
b7c3fee
 
 
cec8267
b7c3fee
 
cec8267
1f9050d
cec8267
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
#!/usr/bin/env bun

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { SSEServerTransport } from "@modelcontextprotocol/sdk/server/sse.js";
import { z } from "zod";
import {
  CallToolRequestSchema,
  ListToolsRequestSchema,
  Tool,
} from "@modelcontextprotocol/sdk/types.js";
import { createServer, IncomingMessage, ServerResponse } from "node:http";
import { URL } from "node:url";
import { searchDatasets, fetchDatasetAggregate, textContent } from "./utils.ts";

const SearchSchema = z.object({
  query: z
    .string()
    .describe(
      "Search query for datasets (e.g., 'nlp sentiment analysis', 'computer vision', 'question answering')",
    ),
});

const FetchSchema = z.object({
  id: z
    .string()
    .describe(
      "Unique dataset identifier (e.g., 'squad', 'imdb', 'cfahlgren1/hub-stats')",
    ),
});

const TOOL_DEFS: Tool[] = [
  {
    name: "search",
    description: "Search for datasets on Hugging Face Hub",
    inputSchema: {
      type: "object",
      properties: {
        query: {
          type: "string",
          description:
            "Search query for datasets (e.g., 'nlp sentiment analysis', 'computer vision', 'question answering')",
        },
      },
      required: ["query"],
    },
  },
  {
    name: "fetch",
    description:
      "Retrieve full information and sample data for a specific dataset",
    inputSchema: {
      type: "object",
      properties: {
        id: {
          type: "string",
          description:
            "Unique dataset identifier (e.g., 'squad', 'imdb', 'cfahlgren1/hub-stats')",
        },
      },
      required: ["id"],
    },
  },
];

const server = new Server(
  { name: "dataset-viewer-mcp", version: "1.0.0" },
  { capabilities: { tools: {} } }
);

server.setRequestHandler(ListToolsRequestSchema, async () => ({ tools: TOOL_DEFS }));

server.setRequestHandler(CallToolRequestSchema, async (request) => {
  const { name, arguments: args } = request.params;

  try {
    switch (name) {
      case "search": {
        const validatedArgs = SearchSchema.parse(args);
        const { query } = validatedArgs;

        const results = await searchDatasets(query);
        return textContent({ results });
      }

      case "fetch": {
        const validatedArgs = FetchSchema.parse(args);
        const { id: datasetId } = validatedArgs;

        const fetchResult = await fetchDatasetAggregate(datasetId);
        return textContent(fetchResult);
      }
      
      default:
        throw new Error(`Unknown tool: ${name}`);
    }
  } catch (error) {
    return {
      content: [{ type: "text", text: `Error: ${error instanceof Error ? error.message : String(error)}` }],
      isError: true,
    };
  }
});

async function main() {
  const port = Number(process.env.PORT) || 3000;
  const transports = new Map<string, SSEServerTransport>();
  
  const httpServer = createServer(async (req: IncomingMessage, res: ServerResponse) => {
    res.setHeader("Access-Control-Allow-Origin", "*");
    res.setHeader("Access-Control-Allow-Headers", "Content-Type");
    res.setHeader("Access-Control-Allow-Methods", "GET, POST, OPTIONS");
    
    const url = new URL(req.url || "", `http://localhost:${port}`);
    
    if (req.method === "OPTIONS") {
      res.writeHead(204);
      res.end();
      return;
    }
    
    if (url.pathname === "/sse") {
      if (req.method === "GET") {
        const transport = new SSEServerTransport("/sse", res);
        transport.onclose = () => transports.delete(transport.sessionId);
        await server.connect(transport);
        transports.set(transport.sessionId, transport);
        return;
      }
      
      if (req.method === "POST") {
        const sessionId = url.searchParams.get("sessionId");
        if (!sessionId) {
          res.writeHead(400).end("Missing sessionId");
          return;
        }
        
        const transport = transports.get(sessionId);
        if (!transport) {
          res.writeHead(404).end("Session not found");
          return;
        }
        
        try {
          await transport.handlePostMessage(req, res);
        } catch (error) {
          console.error("Error handling POST message:", error);
          if (!res.headersSent) {
            res.writeHead(500).end("Internal Server Error");
          }
        }
        return;
      }
    }
    
    res.writeHead(200, { "Content-Type": "application/json" });
    res.end(JSON.stringify({
      name: "Dataset Viewer MCP Server",
      version: "1.0.0",
      transport: "SSE",
      endpoint: "/sse",
      usage: "GET /sse for SSE connection, POST /sse?sessionId=<id> for messages"
    }));
  });
  
  httpServer.listen(port, () => {
    console.log(`Dataset Viewer MCP server running on http://localhost:${port}/sse`);
  });
}

main().catch((error) => {
  console.error("Server error:", error);
  process.exit(1);
});