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ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp

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This MCP server enables users to perform scientific computations regarding linear algebra and vect…

Code source Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http aman-amith-shastry-scientific-computatio 'https://server.smithery.ai/@Aman-Amith-Shastry/scientific_computation_mcp/mcp' --header 'Authorization: <Bearer token for Smithery authentication>'
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "aman-amith-shastry-scientific-computatio": {
            "type": "http",
            "url": "https://server.smithery.ai/@Aman-Amith-Shastry/scientific_computation_mcp/mcp",
            "headers": {
                "Authorization": "<Bearer token for Smithery authentication>"
            }
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Scientific Computation MCP
  2. Installation Guide
  3. Running Locally
  4. Deployment
  5. Components of the Server

Scientific Computation MCP

Installation Guide

The server speaks streamable HTTP. Add it from Smithery with the Smithery CLI (Node 20+):

npm install -g smithery@latest
smithery mcp add @aman-amith-shastry/scientific_computation_mcp --client claude

The namespace is lowercase. Smithery's registry lookup is case-sensitive, and the mixed-case spelling resolves to an empty record with no tools rather than failing outright, so a capitalized name looks like a server with no capabilities.

Swap --client cursor for Cursor, or drop --client to add it as a remote Smithery connection. Restart the client afterwards so it picks up the server.

Running Locally

uv sync
uv run src/main.py

The MCP endpoint is at http://localhost:8081/mcp and a liveness probe at http://localhost:8081/health. Environment overrides: PORT, HOST, MCP_PATH, ALLOWED_ORIGINS, LOG_LEVEL.

Deployment

Smithery no longer builds or hosts containers — servers are published either as a URL that Smithery's gateway proxies to, or as an MCPB bundle for local stdio. This server is published by URL, so the container runs on any host that can serve HTTPS.

docker build -t scientific-computation-mcp .
docker run -p 8081:8081 -e PORT=8081 scientific-computation-mcp

Two constraints the host must satisfy:

  • One instance. Tensors live in process memory between tool calls, so scaling past a single replica splits the store and breaks create_tensor → view_tensor flows.
  • Sessions must survive. The transport runs stateful (stateless_http=False) and the tensor store is keyed per MCP session, which is what keeps concurrent users from reading each other's tensors.
Hosting on Render

render.yaml deploys the Dockerfile as a single free-plan web service. In the Render dashboard: New → Blueprint, then select this repo. Render injects PORT, terminates TLS, and probes /health; no other configuration is required.

Free instances spin down after 15 minutes without inbound traffic and take roughly a minute to come back. An open MCP session does not prevent this: the streamable-HTTP stream is server-to-client, so an idle session sends nothing inbound and the service sleeps out from under it. Two consequences worth planning around:

  • Tensors do not survive a 15-minute gap between tool calls. The store is in process memory, so a spin-down takes the session and its tensors together. Active use keeps the service up, since each tool call is inbound traffic; a long pause mid-analysis does not.
  • Publish-time scans can land on a sleeping instance. Smithery scans the URL as SmitheryBot/1.0, and a cold start can outrun its timeout. Warm /health first.

The free tier also grants 750 instance-hours per workspace per month against a ~730-hour month, so one continuously running free service just fits and a second does not.

Any host that keeps one process always on avoids all of this — the container is plain HTTP on $PORT with no platform-specific assumptions.

Publishing
curl -sS -o /dev/null -w '%{http_code}\n' https://<your-host>/health
smithery mcp publish "https://<your-host>/mcp" -n @aman-amith-shastry/scientific_computation_mcp

The server takes no user configuration, so no config schema is needed.

Components of the Server

Tools
Tensor storage
Linear Algebra
Vector Calculus
Visualization

Questions fréquentes

Qu'est-ce que ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp ?

This MCP server enables users to perform scientific computations regarding linear algebra and vect…

Comment installer ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http aman-amith-shastry-scientific-computatio 'https://server.smithery.ai/@Aman-Amith-Shastry/scientific_computation_mcp/mcp' --header 'Authorization: <Bearer token for Smithery authentication>'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp ?

Oui. Il attend Authorization, à renseigner dans sa configuration.

ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient ai.smithery/Aman-Amith-Shastry-scientific_computation_mcp ?

Il est publié par Aman-Amith-Shastry. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.