Semgrep MCP

Semgrep is an application-security platform for scanning first-party code, open-source dependencies, and hardcoded secrets. Its differentiator is a syntax-aware rule engine with community and organization-authored rules. The fetched vendor pages identify Semgrep Code for SAST, Supply Chain for dependency risk, Secrets, Guardian for AI-generated code, and agentic workflows combining static analysis with AI. Its MCP server gives compatible coding assistants structured access to findings; it does not make a model a security authority.

Pricing and capabilities

The September 2026 pricing page lists Community Code and Supply Chain at $0 per month per contributor. Teams starts at $30 per month per contributor for Code and Supply Chain, while Secrets is shown at $15 per contributor. Teams includes 20 remediation-AI credits per developer monthly. Enterprise is quote-based and advertises 50 AI credits per developer monthly plus optional dedicated infrastructure. Confirm bundles because using several products can cost more than the headline rate.

A security engineer can start with Registry rules, write an internal rule for a dangerous API, test it in Playground, and enforce it on pull requests. Supply Chain checks vulnerable or malicious packages; Secrets looks for credentials. Compared with review conversation from CodeRabbit, Semgrep centers repeatable security policy. Teams should compare Agent Security Suite, CodiumAI, and the AI agent security checklist.

Honest assessment

Breadth and the $0 pilot tier are strengths. The costs are contributor-based, findings can create noise, suppressions need governance, and rules can become stale. MCP may expose repository and vulnerability context, so use narrow credentials and human approval. Test 10 repositories, seed known code, package, and secret issues, then measure recall, true-positive rate among the top 50 findings, CI duration, and triage minutes. Semgrep fits teams prepared to own policy and remediation; without ownership it can merely create a larger queue.

Practical evaluation

Run a two-week pilot on one bounded workflow before granting broad access. Use at least 30 representative tasks, including invalid input, permission failures, stale records, provider timeouts, and recovery cases. Record completion rate, factual or technical correctness, p50 and p95 latency, human review minutes, and total cost per accepted result. Start with read-only scopes and a test workspace where possible. Inspect the exact tools exposed to an agent, then add write access only after an owner defines approval, audit, and rollback procedures. Confirm retention, regional processing, subprocessors, data export, rate limits, support terms, and whether customer content is used for model training.

Build an annual cost model from real volume. Include subscriptions, metered usage, implementation, identity administration, monitoring, reviewer labor, and incident response. Add a 25% volume buffer and test cancellation or export before committing. A purchase is justified when the measured time and risk reduction exceed those costs; a polished demo alone is not evidence of production value.