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import os
import argparse
import subprocess
import json
from pathlib import Path
from typing import Dict, List, Optional
from bioinfomcp_converter import BioinfoMCP
def generate_requirements_with_pipreqs(tool_name, server_path):
"""
Use pipreqs to generate requirements.txt (fallback to minimal deps when pipreqs fails).
"""
_ = tool_name
app_path = Path(server_path) / "app"
target_path = app_path if app_path.exists() else Path(server_path)
try:
subprocess.run(
["pipreqs", str(target_path), "--force"],
capture_output=True,
text=True,
check=True,
)
print(f"Generated requirements.txt using pipreqs from: {target_path}")
except FileNotFoundError:
req_path = Path(server_path) / "requirements.txt"
req_path.write_text("fastmcp\n", encoding="utf-8")
print("pipreqs not found, generated fallback requirements.txt")
except subprocess.CalledProcessError as exc:
req_path = Path(server_path) / "requirements.txt"
req_path.write_text("fastmcp\n", encoding="utf-8")
stderr = (exc.stderr or "").strip()
stdout = (exc.stdout or "").strip()
detail = stderr or stdout or "no stderr/stdout"
print(f"pipreqs failed ({detail}), generated fallback requirements.txt")
except Exception as exc:
req_path = Path(server_path) / "requirements.txt"
req_path.write_text("fastmcp\n", encoding="utf-8")
print(f"pipreqs failed ({exc}), generated fallback requirements.txt")
return Path(server_path) / "requirements.txt"
def generate_environment_yaml(tool_name, server_path):
"""
generate environment.yaml
"""
result = f"""
name: mcp-tool
channels:
- bioconda
- conda-forge
- defaults
dependencies:
- {tool_name}
- python=3.10
"""
with open(server_path / "environment.yaml", "w") as f:
f.write(result)
print("Generated environment.yaml")
return Path(server_path) / "environment.yaml"
def generate_environment_yml(tool_name, server_path):
"""
Generate requirements.yml
"""
_ = server_path
result = f"""name: {tool_name}_env
channels:
- bioconda
- conda-forge
dependencies:
- python=3.10
- {tool_name}
- pip
"""
return result
def parse_bool(value) -> bool:
if isinstance(value, bool):
return value
if value is None:
return False
return str(value).strip().lower() in ("1", "true", "yes", "y", "on")
def has_existing_server(output_root: Path, tool_name: str) -> Optional[Path]:
server_file = output_root / f"mcp_{tool_name}" / "app" / f"{tool_name}_server.py"
if server_file.exists() and server_file.is_file() and server_file.stat().st_size > 0:
return server_file
return None
def convert_mcptool(tool_name, manual, run_help_command, server_path, converter=None):
converter = converter or BioinfoMCP()
app_path = Path(server_path) / "app"
app_path.mkdir(parents=True, exist_ok=True)
conversion_log: Dict = {
"tool_name": tool_name,
"manual": manual,
"run_help_command": bool(run_help_command),
"status": "failed",
"error": "",
"output_file": "",
}
try:
conv_result = converter.autogenerate_mcp_tool(tool_name, manual, run_help_command)
except Exception as exc:
conversion_log["error"] = f"autogenerate_mcp_tool failed: {exc}"
return conversion_log
retry = 0
while not conv_result[0] and retry < 6:
retry += 1
if conv_result[2] is None:
try:
conv_result = converter.autogenerate_mcp_tool(tool_name, manual, run_help_command)
print(f"{tool_name}: regenerate ({retry})")
except Exception as exc:
conversion_log["error"] = f"regenerate failed (retry={retry}): {exc}"
return conversion_log
else:
try:
conv_result = converter.refine_after_feedback(tool_name, code=conv_result[2], error_message=conv_result[1])
print(f"{tool_name}: refine ({retry})")
except Exception as exc:
conversion_log["error"] = f"refine failed (retry={retry}): {exc}"
return conversion_log
if not conv_result[0] or conv_result[2] is None:
conversion_log["error"] = conv_result[1] or "Unknown conversion failure"
return conversion_log
output_path = Path(server_path) / "app" / f"{tool_name}_server.py"
output_path.write_text(conv_result[2], encoding="utf-8")
conversion_log["status"] = "success"
conversion_log["output_file"] = str(output_path)
return conversion_log
def load_tool_list_from_json(json_path: Path, top_k: int = 0, domains: Optional[List[str]] = None) -> List[str]:
with open(json_path, "r", encoding="utf-8") as f:
rows = json.load(f)
if not isinstance(rows, list):
raise ValueError(f"Expected list JSON: {json_path}")
domains = [d.strip().lower() for d in (domains or []) if d.strip()]
tools: List[str] = []
for row in rows:
if not isinstance(row, dict):
continue
if domains:
domain = str(row.get("domain", "")).strip().lower()
if domain not in domains:
continue
package_name = str(row.get("package_name", "")).strip()
software_name = str(row.get("software_name", "")).strip()
tool_name = package_name or software_name
if tool_name:
tools.append(tool_name)
deduped = list(dict.fromkeys(tools))
if top_k > 0:
deduped = deduped[:top_k]
return deduped
def load_jobs_from_json(json_path: Path, top_k: int = 0, domains: Optional[List[str]] = None) -> List[Dict]:
with open(json_path, "r", encoding="utf-8") as f:
rows = json.load(f)
if not isinstance(rows, list):
raise ValueError(f"Expected list JSON: {json_path}")
domains = [d.strip().lower() for d in (domains or []) if d.strip()]
jobs: List[Dict] = []
for row in rows:
if not isinstance(row, dict):
continue
name = (
str(row.get("name", "")).strip()
or str(row.get("package_name", "")).strip()
or str(row.get("software_name", "")).strip()
)
if not name:
continue
domain = str(row.get("domain", "")).strip().lower()
if domains and domain not in domains:
continue
jobs.append(
{
"name": name,
"manual": str(row.get("manual", "--help")),
"run_help_command": parse_bool(row.get("run_help_command", True)),
"domain": domain,
"tier": str(row.get("tier", "")),
}
)
if top_k > 0:
jobs = jobs[:top_k]
return jobs
def load_jobs_from_manual_dir(manual_dir: Path, top_k: int = 0) -> List[Dict]:
"""
Load conversion jobs from a directory containing *.help.txt or *.manual_bundle.txt.
"""
if not manual_dir.exists():
raise FileNotFoundError(f"Manual directory not found: {manual_dir}")
candidates = sorted(
list(manual_dir.glob("*.help.txt")) + list(manual_dir.glob("*.manual_bundle.txt"))
)
# De-duplicate while preferring manual_bundle when both exist.
by_tool: Dict[str, Path] = {}
for p in candidates:
name = p.name
if name.endswith(".manual_bundle.txt"):
tool_name = name[: -len(".manual_bundle.txt")]
by_tool[tool_name] = p
elif name.endswith(".help.txt"):
tool_name = name[: -len(".help.txt")]
by_tool.setdefault(tool_name, p)
jobs: List[Dict] = []
for tool_name, manual_path in sorted(by_tool.items()):
jobs.append(
{
"name": tool_name,
"manual": str(manual_path),
"run_help_command": False,
"domain": "",
"tier": "",
}
)
if top_k > 0:
jobs = jobs[:top_k]
return jobs
def select_jobs_for_shard(jobs: List[Dict], shard_count: int, shard_index: int) -> List[Dict]:
"""
Deterministically split jobs for multi-terminal parallel execution.
"""
if shard_count <= 1:
return jobs
if shard_index < 0 or shard_index >= shard_count:
raise ValueError(f"Invalid shard_index={shard_index}. Expected 0 <= shard_index < {shard_count}")
selected: List[Dict] = []
for idx, job in enumerate(jobs):
if idx % shard_count == shard_index:
selected.append(job)
return selected
def dockerfile_content(tool_name):
return f"""
FROM python:3.10-slim
# Install system dependencies
RUN apt-get update && \
apt-get install -y \
default-jre \
wget \
curl \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# Install Miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && \
bash /tmp/miniconda.sh -b -p /opt/conda && \
rm /tmp/miniconda.sh
# Add conda to PATH
ENV PATH="/opt/conda/bin:$PATH"
# Install {tool_name} via conda (e.g., from bioconda)
RUN conda install -c bioconda {tool_name} -y && \
conda clean -a
# Install Python dependencies
RUN pip install uv
RUN uv pip install --system fastmcp
# Create app directory
WORKDIR /app
# Copy your MCP server
COPY app/{tool_name}_server.py /app/
# Create workspace and output directories
RUN mkdir -p /app/workspace /app/output
# Make sure the server script is executable
RUN chmod +x /app/{tool_name}_server.py
# Expose port for MCP over HTTP (optional)
EXPOSE 8000
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD python -c "import sys; sys.exit(0)"
# Default command runs the MCP server via stdio
CMD ["python", "/app/{tool_name}_server.py"]
"""
def dockercompose_content(tool_name):
"""Generate docker-compose.yml for easy deployment"""
compose = f"""version: '3.8'
services:
mcp-{tool_name}:
build: .
image: mcp-{tool_name}:latest
container_name: mcp-{tool_name}
ports:
- "8000:8000"
environment:
- MCP_SERVER_NAME={tool_name}
volumes:
- ./workspace:/app/workspace
- ./output:/app/output
restart: unless-stopped
healthcheck:
test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
interval: 30s
timeout: 10s
retries: 3
start_period: 5s
"""
return compose
def image_name_for_tool(tool_name: str) -> str:
return f"mcp-{tool_name}:latest"
def build_docker_image(tool_name, server_path, output_path, is_pipeline):
# Create build directory
try:
_ = output_path
df_content = dockerfile_content(tool_name)
with open(server_path / "Dockerfile", "w") as f:
f.write(df_content)
# make the docker-compose.yml
if not is_pipeline:
dc_content = dockercompose_content(tool_name)
with open(server_path/"docker-compose.yml", "w") as f:
f.write(dc_content)
# subprocess.run(["docker", "build", "-t", f"{args.name}-docker", server_path])
return 1
except:
return 0
def claude_addition(tool_name, server_path):
image_name = image_name_for_tool(tool_name)
workspace_path = str((Path(server_path) / "workspace").resolve())
config = {
"mcpServers": {
tool_name: {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-v",
f"{workspace_path}:/app/workspace",
image_name
]
}
}
}
return json.dumps(config, indent=2)
if __name__ == '__main__':
parser = argparse.ArgumentParser("Accept the Bioinformatic tool name and the help document")
parser.add_argument('--model', type=str, default='openai', choices=['openai', 'azure', 'gemini'], help="LLM backend")
parser.add_argument('--name', type=str)
parser.add_argument('--manual', type=str, default='--help', help="The file path to the help document or help flag")
parser.add_argument('--run_help_command', type=str, default='True')
parser.add_argument('--output_location', type=str, required=True)
parser.add_argument('--is_pipeline', action='store_true', default=False)
parser.add_argument('--tools_json', type=str, default="", help="JSON list file from crawler output")
parser.add_argument('--jobs_json', type=str, default="", help="Per-tool jobs JSON with name/manual/run_help_command")
parser.add_argument('--manual_dir', type=str, default="", help="Directory containing *.help.txt or *.manual_bundle.txt")
parser.add_argument('--top_k', type=int, default=0, help="Only convert first K tools from tools_json/jobs_json")
parser.add_argument('--domains', nargs='*', default=[], help="Domain filter for tools_json/jobs_json")
parser.add_argument('--skip_existing', type=str, default='True', help="Skip tool if MCP server file already exists")
parser.add_argument('--shard_count', type=int, default=1, help="Total shards for multi-terminal execution")
parser.add_argument('--shard_index', type=int, default=0, help="Current shard index in [0, shard_count)")
parser.add_argument('--report_suffix', type=str, default="", help="Optional suffix for report filename")
args = parser.parse_args()
output_root = Path(args.output_location)
output_root.mkdir(parents=True, exist_ok=True)
run_help_command = parse_bool(args.run_help_command)
skip_existing = parse_bool(args.skip_existing)
converter = BioinfoMCP(model=args.model)
jobs: List[Dict] = []
if args.jobs_json:
jobs = load_jobs_from_json(Path(args.jobs_json), top_k=args.top_k, domains=args.domains)
elif args.manual_dir:
jobs = load_jobs_from_manual_dir(Path(args.manual_dir), top_k=args.top_k)
elif args.tools_json:
tools = load_tool_list_from_json(Path(args.tools_json), top_k=args.top_k, domains=args.domains)
jobs = [{"name": t, "manual": args.manual, "run_help_command": run_help_command} for t in tools]
elif args.name:
jobs = [{"name": args.name, "manual": args.manual, "run_help_command": run_help_command}]
else:
raise ValueError("Either --name, --tools_json, --jobs_json or --manual_dir must be provided")
if args.shard_count < 1:
raise ValueError(f"--shard_count must be >= 1, got: {args.shard_count}")
jobs = select_jobs_for_shard(jobs, args.shard_count, args.shard_index)
print(f"Shard selection: shard_index={args.shard_index}/{args.shard_count}, jobs={len(jobs)}")
run_log: List[Dict] = []
for job in jobs:
tool_name = job["name"]
manual = job.get("manual", "--help")
job_run_help = parse_bool(job.get("run_help_command", True))
existing_server = has_existing_server(output_root, tool_name) if skip_existing else None
if existing_server:
print(f"Skip existing MCP server: {existing_server}")
run_log.append(
{
"tool_name": tool_name,
"manual": manual,
"run_help_command": bool(job_run_help),
"status": "skipped_existing",
"error": "",
"output_file": str(existing_server),
"dockerfile_ready": True,
}
)
continue
server_path = output_root / f"mcp_{tool_name}"
os.makedirs(server_path, exist_ok=True)
print("Server path", server_path)
app_path = Path(server_path) / "app"
os.makedirs(app_path, exist_ok=True)
result = convert_mcptool(tool_name, manual, job_run_help, server_path, converter=converter)
if result.get("status") == "success":
generate_requirements_with_pipreqs(tool_name, server_path)
generate_environment_yaml(tool_name, server_path)
status = build_docker_image(tool_name, server_path, output_root, args.is_pipeline)
result["dockerfile_ready"] = bool(status)
if status:
add = claude_addition(tool_name, server_path)
print(f"Add the following onto your Claude Configuration json file to run the MCP server:\n{'=='*10}\n{add}\n{'=='*10}")
else:
print("Failed to build Docker Image")
else:
result["dockerfile_ready"] = False
print(f"Skip packaging for {tool_name}: conversion failed -> {result.get('error', '')}")
run_log.append(result)
report_name = "conversion_report.json"
if args.shard_count > 1:
report_name = f"conversion_report.shard_{args.shard_index}_of_{args.shard_count}.json"
if args.report_suffix:
report_name = report_name.replace(".json", f".{args.report_suffix}.json")
report_path = output_root / report_name
report_path.write_text(json.dumps(run_log, ensure_ascii=False, indent=2), encoding="utf-8")
print(f"Saved conversion report to: {report_path}")