Investment discipline MCP server with RAG, behavior detection, journaling, and market data.
Investbrain MCP server exists for a simple reason — assistants are far more useful when they can act on Investbrain directly instead of describing what you should do. Investment discipline MCP server with RAG, behavior detection, journaling, and market data.
启动后 Server 会以 stdio 方式接受 MCP 客户端调用。配置 Claude Desktop 见下方 Claude Desktop 接入。
The server ships on npm as npm, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
You will need 4 environment variables: DEEPSEEK_API_KEY, TUSHARE_TOKEN, DASHSCOPE_API_KEY, AGAINST_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. It is maintained by com.mangofolio; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Investbrain's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
{
"mcpServers": {
"investbrain": {
"command": "python",
"args": [
"D:/claudework/investbrain/src/mcp_server/server.py"
],
"env": {
"DEEPSEEK_API_KEY": "sk-your-key-here"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| DEEPSEEK_API_KEY | Credential the server authenticates with. | Yes |
| TUSHARE_TOKEN | Credential the server authenticates with. | Yes |
| DASHSCOPE_API_KEY | Credential the server authenticates with. | Yes |
| AGAINST_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.