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"""
Model Context Protocol (MCP) for TISSUE
TISSUE (Transcript Imputation with Spatial Single-cell Uncertainty Estimation) provides methods for spatial gene expression prediction and uncertainty quantification in spatial transcriptomics data. It enables uncertainty-aware analysis including multiple imputation, cell filtering, and weighted PCA for improved downstream analysis.
This MCP Server contains the tools extracted from the following tutorials:
1. tissue
- predict_spatial_gene_expression: Predict spatial gene expression using paired spatial and scRNA-seq data
- calibrate_uncertainties_and_prediction_intervals: Use TISSUE to calibrate uncertainties and obtain prediction intervals
- multiple_imputation_hypothesis_testing: Hypothesis testing with TISSUE multiple imputation framework
- tissue_cell_filtering_for_supervised_learning: TISSUE cell filtering for supervised learning applications
- tissue_cell_filtering_for_pca: TISSUE cell filtering for PCA, clustering and visualization
- tissue_weighted_pca: TISSUE-WPCA (weighted principal component analysis)
"""
import sys
from pathlib import Path
from fastmcp import FastMCP
# Import the MCP tools from the tools folder
from tools.tissue_readme import tissue_mcp
from starlette.requests import Request
from starlette.responses import PlainTextResponse, JSONResponse
import os
from fastapi.staticfiles import StaticFiles
import uuid
# Define the MCP server
mcp = FastMCP(name = "TISSUE")
# Mount the tools
mcp.mount(tissue_mcp)
# Use absolute directory for uploads
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
UPLOAD_DIR = os.path.join(BASE_DIR, "/data/upload")
os.makedirs(UPLOAD_DIR, exist_ok=True)
@mcp.custom_route("/health", methods=["GET"])
async def health_check(request: Request) -> PlainTextResponse:
return PlainTextResponse("OK")
@mcp.custom_route("/", methods=["GET"])
async def index(request: Request) -> PlainTextResponse:
return PlainTextResponse("MCP is on https://Paper2Agent-tissue-mcp.hf.space/mcp")
# Upload route
@mcp.custom_route("/upload", methods=["POST"])
async def upload(request: Request):
form = await request.form()
up = form.get("file")
if up is None:
return JSONResponse({"error": "missing form field 'file'"}, status_code=400)
# Generate a safe filename
orig = getattr(up, "filename", "") or ""
ext = os.path.splitext(orig)[1]
name = f"{uuid.uuid4().hex}{ext}"
dst = os.path.join(UPLOAD_DIR, name)
# up is a Starlette UploadFile-like object
with open(dst, "wb") as out:
out.write(await up.read())
# Return only the absolute local path
abs_path = os.path.abspath(dst)
return JSONResponse({"path": abs_path})
app = mcp.http_app(path="/mcp")
# Saved uploaded input files
app.mount("/files", StaticFiles(directory=UPLOAD_DIR), name="files")
# Saved output files
app.mount("/outputs", StaticFiles(directory="/data/tmp_outputs"), name="outputs")
# Run the MCP server
if __name__ == "__main__":
mcp.run(transport="http", host="127.0.0.1", port=8003) |