Aman Amith Shastry Scientific Computation MCP vs Dingo
A side-by-side look at the Aman Amith Shastry Scientific Computation MCP and Dingo MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Aman Amith Shastry Scientific Computation MCP for data science tools work over a hosted endpoint; choose Dingo for data science tools as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Aman Amith Shastry Scientific Computation MCP when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a remote HTTP/SSE transport.
- You have the keys it needs:
PORT, HOST, MCP_PATH, ALLOWED_ORIGINS, LOG_LEVEL. - You want tools like
create_tensor, view_tensor, delete_tensor.
Choose Dingo when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Science Tools | Data Science Tools |
| Quality signal | 51/100 · Good | 60/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Remote HTTP/SSE | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | PORTHOSTMCP_PATHALLOWED_ORIGINSLOG_LEVEL | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 3 | 759 |
| Directory activity | 1 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | 28 | Not listed |
| Full listing | View Aman Amith Shastry Scientific Computation MCP | View Dingo |
Tools & capabilities
Aman Amith Shastry Scientific Computation MCP tools 28
create_tensorview_tensordelete_tensoradd_matricessubtract_matricesmultiply_matricesscale_matrixmatrix_inversetransposedeterminantrankcompute_eigen- +16 more on the listing page
Dingo tools
No tool names declared yet. Check the project README from the listing page.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Aman Amith Shastry Scientific Computation MCP
{
"mcpServers": {
"aman-amith-shastry-scientific-computation-mcp": {
"url": "http://localhost:8081/mcp"
}
}
}
Dingo
{
"mcpServers": {
"dataeval-dingo": {
"command": "uvx",
"args": [
"dingo-python"
]
}
}
}
Frequently asked questions
Aman Amith Shastry Scientific Computation MCP is categorized under Data Science Tools and uses a remote HTTP/SSE transport. Dingo belongs to Data Science Tools and uses a local stdio subprocess. Pick Aman Amith Shastry Scientific Computation MCP for data science tools work and Dingo for data science tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Aman Amith Shastry Scientific Computation MCP has no declared pricing — check the project's own site. Dingo is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add aman-amith-shastry-scientific-computation-mcp and dataeval-dingo as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Aman Amith Shastry Scientific Computation MCP has a quality signal of 51/100 (Good) with 1 views, 0 installs and 3 GitHub stars. Dingo has 60/100 (Good) with 5 views, 0 installs and 759 GitHub stars.