build(deps): bump mcp from 1.12.4 to 1.19.0

Bumps [mcp](https://github.com/modelcontextprotocol/python-sdk) from 1.12.4 to 1.19.0.
- [Release notes](https://github.com/modelcontextprotocol/python-sdk/releases)
- [Changelog](https://github.com/modelcontextprotocol/python-sdk/blob/main/RELEASE.md)
- [Commits](https://github.com/modelcontextprotocol/python-sdk/compare/v1.12.4...v1.19.0)

---
updated-dependencies:
- dependency-name: mcp
  dependency-version: 1.19.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

Dockerfile

@@ -19,6 +19,10 @@ RUN poetry lock
 
 # Install dependencies
 RUN poetry export -f requirements.txt --without-hashes -o requirements.txt
+
+# Install wheel (required to build packages like fire)
+RUN pip install --upgrade pip setuptools wheel
+
 RUN pip install --no-cache-dir -r requirements.txt
 
 # Runtime stage

Readme.md

@@ -21,9 +21,7 @@
   <a href="https://pypi.org/project/agentic-security/">
     <img alt="PyPI Version" src="https://img.shields.io/pypi/v/agentic-security?style=for-the-badge&logo=pypi&labelColor=000000&color=00CCFF" />
   </a>
-  <a href="https://discord.gg/stw3DfZQ">
-    <img alt="Join Discord" src="https://img.shields.io/badge/Discord-Join%20Us-black?style=for-the-badge&logo=discord&labelColor=000000&color=DD55FF" />
-  </a>
+
 </p>
 
 

agentic_security/mcp/client.py

@@ -3,6 +3,8 @@ import asyncio
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
 
+from agentic_security.logutils import logger
+
 # Create server parameters for stdio connection
 server_params = StdioServerParameters(
     command="python",  # Executable
@@ -12,42 +14,54 @@ server_params = StdioServerParameters(
 
 
 async def run() -> None:
-    async with stdio_client(server_params) as (read, write):
-        async with ClientSession(read, write) as session:
-            # Initialize the connection --> connection does not work
-            await session.initialize()
+    try:
+        logger.info(
+            "Starting stdio client session with server parameters: %s", server_params
+        )
+        async with stdio_client(server_params) as (read, write):
+            async with ClientSession(read, write) as session:
+                # Initialize the connection --> connection does not work
+                logger.info("Initializing client session...")
+                await session.initialize()
 
-            # List available prompts, resources, and tools --> no avalialbe tools
-            prompts = await session.list_prompts()
-            print(f"Available prompts: {prompts}")
+                # List available prompts, resources, and tools --> no avalialbe tools
+                logger.info("Listing available prompts...")
+                prompts = await session.list_prompts()
+                logger.info(f"Available prompts: {prompts}")
 
-            resources = await session.list_resources()
-            print(f"Available resources: {resources}")
+                logger.info("Listing available resources...")
+                resources = await session.list_resources()
+                logger.info(f"Available resources: {resources}")
 
-            tools = await session.list_tools()
-            print(f"Available tools: {tools}")
+                logger.info("Listing available tools...")
+                tools = await session.list_tools()
+                logger.info(f"Available tools: {tools}")
 
-            # Call the echo tool --> echo tool iisue
-            echo_result = await session.call_tool(
-                "echo_tool", arguments={"message": "Hello from client!"}
-            )
-            print(f"Tool result: {echo_result}")
+                # Call the echo tool --> echo tool issue
+                logger.info("Calling echo_tool with message...")
+                echo_result = await session.call_tool(
+                    "echo_tool", arguments={"message": "Hello from client!"}
+                )
+                logger.info(f"Tool result: {echo_result}")
 
-            # # Read the echo resource
-            # echo_content, mime_type = await session.read_resource(
-            #     "echo://Hello_resource"
-            # )
-            # print(f"Resource content: {echo_content}")
-            # print(f"Resource MIME type: {mime_type}")
+                # # Read the echo resource
+                # echo_content, mime_type = await session.read_resource(
+                #     "echo://Hello_resource"
+                # )
+                # logger.info(f"Resource content: {echo_content}")
+                # logger.info(f"Resource MIME type: {mime_type}")
 
-            # # Get and use the echo prompt
-            # prompt_result = await session.get_prompt(
-            #     "echo_prompt", arguments={"message": "Hello prompt!"}
-            # )
-            # print(f"Prompt result: {prompt_result}")
+                # # Get and use the echo prompt
+                # prompt_result = await session.get_prompt(
+                #     "echo_prompt", arguments={"message": "Hello prompt!"}
+                # )
+                # logger.info(f"Prompt result: {prompt_result}")
 
-            # You can perform additional operations here as needed
-            return prompts, resources, tools
+                logger.info("Client operations completed successfully.")
+                return prompts, resources, tools
+    except Exception as e:
+        logger.error(f"An error occurred during client operations: {e}", exc_info=True)
+        raise
 
 
 if __name__ == "__main__":

agentic_security/mcp/main.py

@@ -4,7 +4,6 @@ from mcp.server.fastmcp import FastMCP
 # Initialize MCP server
 mcp = FastMCP(
     name="Agentic Security MCP Server",
-    description="MCP server to interact with LLM scanning test",
     dependencies=["httpx"],
 )
 

agentic_security/probe_data/data.py

@@ -8,7 +8,6 @@ from typing import Any, TypeVar
 import httpx
 import pandas as pd
 from cache_to_disk import cache_to_disk
-from datasets import load_dataset
 
 from agentic_security.logutils import logger
 from agentic_security.probe_data import stenography_fn
@@ -20,6 +19,7 @@ from agentic_security.probe_data.modules import (
     inspect_ai_tool,
     rl_model,
 )
+from datasets import load_dataset
 
 # Type aliases for clarity
 T = TypeVar("T")
@@ -245,61 +245,47 @@ def load_jailbreak_v28k() -> ProbeDataset:
         return create_probe_dataset("JailbreakV-28K/JailBreakV-28k", [])
 
 
-@cache_to_disk()
-def load_local_csv() -> ProbeDataset:
-    """Load prompts from local CSV files."""
-    csv_files = [f for f in os.listdir(".") if f.endswith(".csv")]
-    logger.info(f"Found {len(csv_files)} CSV files: {csv_files}")
-
-    prompts = []
-    for file in csv_files:
-        try:
-            df = pd.read_csv(file)
-            if "prompt" in df.columns:
-                prompts.extend(df["prompt"].tolist())
-            else:
-                logger.warning(f"File {file} lacks a suitable prompt column")
-        except Exception as e:
-            logger.error(f"Error reading {file}: {e}")
-
-    return create_probe_dataset("Local CSV", prompts, {"src": str(csv_files)})
-
-
 @cache_to_disk(1)
-def load_csv(file: str) -> ProbeDataset:
-    """Load prompts from local CSV files."""
+def file_dataset(file) -> list[str]:
     prompts = []
     try:
-        df = pd.read_csv(file)
-        prompts = df["prompt"].tolist()
+        df = pd.read_csv(os.path.join("./datasets", file), encoding_errors="ignore")
         if "prompt" in df.columns:
-            prompts.extend(df["prompt"].tolist())
+            prompts = df["prompt"].tolist()
         else:
             logger.warning(f"File {file} lacks a suitable prompt column")
     except Exception as e:
         logger.error(f"Error reading {file}: {e}")
+    return prompts
+
+
+def load_local_csv() -> ProbeDataset:
+    """Load prompts from local CSV files."""
+    os.makedirs("./datasets", exist_ok=True)
+    csv_files = [f for f in os.listdir("./datasets") if f.endswith(".csv")]
+    logger.info(f"Found {len(csv_files)} CSV files: {csv_files}")
+
+    prompts = []
+    for file in csv_files:
+        prompts.extend(file_dataset(file))
+    return create_probe_dataset("Local CSV", prompts, {"src": str(csv_files)})
+
+
+def load_csv(file: str) -> ProbeDataset:
+    """Load prompts from local CSV files."""
+    prompts = file_dataset(file)
     return create_probe_dataset(f"fs://{file}", prompts, {"src": str(file)})
 
 
-@cache_to_disk(1)
 def load_local_csv_files() -> list[ProbeDataset]:
     """Load prompts from local CSV files and return a list of ProbeDataset objects."""
-    csv_files = [f for f in os.listdir(".") if f.endswith(".csv")]
+    csv_files = [f for f in os.listdir("./datasets") if f.endswith(".csv")]
     logger.info(f"Found {len(csv_files)} CSV files: {csv_files}")
 
     datasets = []
 
     for file in csv_files:
-        try:
-            df = pd.read_csv(file)
-            if "prompt" in df.columns:
-                prompts = df["prompt"].tolist()
-                datasets.append(create_probe_dataset(file, prompts, {"src": file}))
-            else:
-                logger.warning(f"File {file} lacks a suitable prompt column")
-        except Exception as e:
-            logger.error(f"Error reading {file}: {e}")
-
+        datasets.append(create_probe_dataset(file, file_dataset(file), {"src": file}))
     return datasets
 
 
@@ -336,12 +322,20 @@ class StenographyTransformer:
                 )
                 continue
 
-            size = len(dataset.prompts)
+            # Convert async generator (if any) to a list
+            prompts = (
+                list(dataset.prompts) if hasattr(dataset.prompts, "__iter__") else []
+            )
+            size = len(prompts)
+
+            if size == 0:
+                continue
+
             sample_size = max(1, int(size * 0.25))  # At least 1 sample
 
             for name, fn in self.TRANSFORMATIONS.items():
                 logger.info(f"Applying {name} to {dataset.dataset_name}")
-                sampled = random.sample(dataset.prompts, min(sample_size, size))
+                sampled = random.sample(prompts, min(sample_size, size))
                 try:
                     transformed = [
                         f"Follow the instructions in {name}: {fn(str(p))}"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "agentic_security"
-version = "0.7.2"
+version = "0.7.4"
 description = "Agentic LLM vulnerability scanner"
 authors = ["Alexander Miasoiedov <msoedov@gmail.com>"]
 maintainers = ["Alexander Miasoiedov <msoedov@gmail.com>"]
@@ -28,54 +28,50 @@ agentic_security = "agentic_security.__main__:main"
 
 [tool.poetry.dependencies]
 python = "^3.11"
-fastapi = "^0.115.8"
-uvicorn = "^0.34.0"
+fastapi = "^0.116.1"
+uvicorn = "^0.35.0"
 fire = "0.7.0"
 loguru = "^0.7.3"
 httpx = "^0.28.1"
 cache-to-disk = "^2.0.0"
 pandas = ">=1.4,<3.0"
-datasets = "^3.3.0"
+datasets = "^4.0.0"
 tabulate = ">=0.8.9,<0.10.0"
 colorama = "^0.4.4"
-matplotlib = "^3.9.2"
-pydantic = "2.10.6"
+matplotlib = "^3.10.5"
+pydantic = "^2.11.7"
 scikit-optimize = "^0.10.2"
-scikit-learn = "1.6.1"
+scikit-learn = "^1.7.1"
 numpy = ">=1.24.3,<3.0.0"
 jinja2 = "^3.1.4"
 python-multipart = "^0.0.20"
 tomli = "^2.2.1"
-rich = "13.9.4"
+rich = "^14.1.0"
 gTTS = "^2.5.4"
-sentry_sdk = "^2.22.0"
-orjson = "^3.10"
-pyfiglet = "^1.0.2"
-termcolor = "^2.4.0"
-mcp = "^1.4.1"
-
+sentry_sdk = "^2.34.1"
+orjson = "^3.11.2"
+pyfiglet = "^1.0.3"
+termcolor = "^3.1.0"
+mcp = "^1.12.4"
 # garak = { version = "*", optional = true }
-pytest-xdist = "3.6.1"
-
+pytest-xdist = "^3.8.0"
 
 [tool.poetry.group.dev.dependencies]
 # Pytest
-pytest = "^8.3.4"
-pytest-asyncio = "^0.25.2"
-inline-snapshot = ">=0.13.3,<0.21.0"
+pytest = "^8.4.1"
+pytest-asyncio = "^1.1.0"
+inline-snapshot = ">=0.13.3,<0.27.2"
 pytest-httpx = "^0.35.0"
-pytest-mock = "^3.14.0"
-
+pytest-mock = "^3.14.1"
 # Rest
 black = ">=24.10,<26.0"
-mypy = "^1.12.0"
-pre-commit = "^4.0.1"
-huggingface-hub = ">=0.25.1,<0.30.0"
-
+mypy = "^1.17.1"
+pre-commit = "^4.3.0"
+huggingface-hub = ">=0.25.1,<0.34.4"
 # Docs
 mkdocs = ">=1.4.2"
-mkdocs-material = "^9.6.4"
-mkdocstrings = ">=0.26.1"
+mkdocs-material = "^9.6.16"
+mkdocstrings = ">=0.29.0"
 mkdocs-jupyter = ">=0.25.1"
 
 

tests/test_registry.py

@@ -1,7 +1,7 @@
 import pytest
-from datasets import load_dataset
 
 from agentic_security.probe_data import REGISTRY
+from datasets import load_dataset
 
 
 @pytest.mark.slow

ui/package-lock.json

@@ -4266,9 +4266,9 @@
       }
     },
     "node_modules/compression": {
-      "version": "1.8.0",
-      "resolved": "https://registry.npmjs.org/compression/-/compression-1.8.0.tgz",
-      "integrity": "sha512-k6WLKfunuqCYD3t6AsuPGvQWaKwuLLh2/xHNcX4qE+vIfDNXpSqnrhwA7O53R7WVQUnt8dVAIW+YHr7xTgOgGA==",
+      "version": "1.8.1",
+      "resolved": "https://registry.npmjs.org/compression/-/compression-1.8.1.tgz",
+      "integrity": "sha512-9mAqGPHLakhCLeNyxPkK4xVo746zQ/czLH1Ky+vkitMnWfWZps8r0qXuwhwizagCRttsL4lfG4pIOvaWLpAP0w==",
       "dev": true,
       "license": "MIT",
       "dependencies": {
@@ -4276,7 +4276,7 @@
         "compressible": "~2.0.18",
         "debug": "2.6.9",
         "negotiator": "~0.6.4",
-        "on-headers": "~1.0.2",
+        "on-headers": "~1.1.0",
         "safe-buffer": "5.2.1",
         "vary": "~1.1.2"
       },
@@ -6891,9 +6891,9 @@
       }
     },
     "node_modules/http-proxy-middleware": {
-      "version": "2.0.7",
-      "resolved": "https://registry.npmjs.org/http-proxy-middleware/-/http-proxy-middleware-2.0.7.tgz",
-      "integrity": "sha512-fgVY8AV7qU7z/MmXJ/rxwbrtQH4jBQ9m7kp3llF0liB7glmFeVZFBepQb32T3y8n8k2+AEYuMPCpinYW+/CuRA==",
+      "version": "2.0.9",
+      "resolved": "https://registry.npmjs.org/http-proxy-middleware/-/http-proxy-middleware-2.0.9.tgz",
+      "integrity": "sha512-c1IyJYLYppU574+YI7R4QyX2ystMtVXZwIdzazUIPIJsHuWNd+mho2j+bKoHftndicGj9yh+xjd+l0yj7VeT1Q==",
       "dev": true,
       "license": "MIT",
       "dependencies": {
@@ -8419,9 +8419,9 @@
       }
     },
     "node_modules/on-headers": {
-      "version": "1.0.2",
-      "resolved": "https://registry.npmjs.org/on-headers/-/on-headers-1.0.2.tgz",
-      "integrity": "sha512-pZAE+FJLoyITytdqK0U5s+FIpjN0JP3OzFi/u8Rx+EV5/W+JTWGXG8xFzevE7AjBfDqHv/8vL8qQsIhHnqRkrA==",
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/on-headers/-/on-headers-1.1.0.tgz",
+      "integrity": "sha512-737ZY3yNnXy37FHkQxPzt4UZ2UWPWiCZWLvFZ4fu5cueciegX0zGPnrlY6bwRg4FdQOe9YU8MkmJwGhoMybl8A==",
       "dev": true,
       "license": "MIT",
       "engines": {