Bring Sast
to LangChain
Create your Vinkius account to connect Semgrep to LangChain and start using all 10 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Semgrep MCP Server?
Connect the Semgrep AppSec platform directly to your AI agent to radically accelerate code security triaging. Instead of forcing developers to jump between their IDE and the Semgrep dashboard, empower your AI to pull 'Findings', analyze the vulnerable syntax, and instantly close false positives.
What you can do
- Triage Findings (Bugs) — Instruct the agent to grab the latest CI vulnerability findings and immediately push a status update to mark it as fixed, ignored, or mitigated (
update_finding_status) - Rule Management — Request the AI to look at a newly discovered bad coding pattern and command it to write and deploy a matching custom semantic rule (
create_rule) to your organizational deployment - Project & Deployment Scoping — Map out all repositories running Semgrep actions and check their overarching security health scores in milliseconds
- Comprehensive Forensics — Fetch granular SCA and SAST semantic flaw definitions, including exact snippets, CVE links, and the specific bad lines causing the trigger
How it works
- Enable this MCP server within your workflow
- Supply a standard API Token from your Semgrep Dashboard settings
- Engage your agent in Cursor or Claude to cross-examine security warnings dynamically
Who is this for?
- Security Engineers (AppSec) — tell the AI to quickly delete an obsolete rule across the entire deployment without wrestling with the dashboard interface
- DevOps — retrieve compliance metrics and pipeline fix rates natively and pipe them directly into an executive summary report via chat
- Software Developers — let Cursor fetch the specific
finding_idblocking your PR, explain what the vulnerability means, and draft the exact semantic fix to pass the scan
Built-in capabilities (10)
Allows developers to forbid project-specific bad patterns securely and continuously across the enterprise repositories. Create a customized Semgrep security rule within the platform
Delete a custom Semgrep security rule from the deployment
Explains the exact malicious code block, suggests semantic fixes, states whether it is blocking PRs in CI, and links to CVE data (if an SCA supply chain defect). Get atomic details for a specific Semgrep flaw
Typically consumed to render executive security dashboards. Get AppSec metrics and compliance stats for Semgrep
Search for a precise Semgrep project by exact repository name
The primary key is the deployment slug identifier. Almost all subsequent API operations targeting rules, projects, or findings will require this deployment slug to define the scope. List Semgrep organizational deployments
Findings provide snippet details, file line numbers, severity, and rule types. Fetch global static analysis security findings for a deployment
Projects maintain a link between developers and static security scan outputs over time. List Semgrep projects (repositories) monitored in a deployment
The rules are structured YAML definitions that search for semantic anti-patterns in codebases (e.g., unparameterized SQL queries, hardcoded AWS keys). List Semgrep semantic rules deployed globally
Valid states generally include active, fixed, false_positive, ignored, mitigated. Resolving findings through this API cleans up the developer experience when managing compliance queues. Mark a Semgrep finding state (e.g., fixed, false positive)
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Semgrep through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Semgrep MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Semgrep queries for multi-turn workflows
Semgrep in LangChain
Why run Semgrep with Vinkius?
The Semgrep connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 10 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Semgrep using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Semgrep and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Semgrep to LangChain through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Semgrep for LangChain
Every request between LangChain and Semgrep is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
Can the AI resolve or close findings in Semgrep natively?
Yes. This server supports mutable actions. By invoking update_finding_status, your AI agent can shift a specific semantic flaw to 'mitigated', 'fixed', 'ignored', or 'false_positive' updating the registry in real-time.
How can I deploy a new custom SAST rule via chat?
Simply ask the LLM: 'Draft a semantic grep rule to ban hardcoded API keys in Python and deploy it'. The agent will natively format the JSON structure required and call create_rule, sending it directly to all repositories.
Do I need to supply a 'Deployment Slug' for every request?
Most API queries require the deployment context. To ensure smooth interactions, just tell the agent your organization slug once (or let it query list_deployments to fetch the default one). The agent will remember it for the rest of the conversation loop.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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