secscan-mcp
The secscan-mcp server provides comprehensive security scanning tools for AI coding assistants, enabling detection of secrets, code vulnerabilities, dependency issues, and IaC misconfigurations.
Secret Detection (
scan_secrets): Scans a directory for hardcoded credentials, with an option to include git commit history.SAST Analysis (
scan_code): Runs static analysis tools (semgrep, bandit) to find code-level security vulnerabilities.Dependency Scanning (
scan_dependencies): Checks lockfiles for known vulnerable packages using osv-scanner.IaC Scanning (
scan_iac): Detects misconfigurations in Infrastructure-as-Code files via checkov.Unified Scanning (
scan_all): Runs all available scanners in one call and produces a consolidated, normalized report.Scanner Discovery (
list_available_scanners): Reports which third-party scanning CLIs are installed and available.Remediation Guidance (
explain_finding): Provides detailed explanations and remediation hints for a specificrule_idfrom scan results.
All scan tools accept a path parameter and an optional severity_threshold (critical, high, medium, low, info) to filter results. The server operates gracefully, skipping optional scanners if their CLIs are not installed, and works with any MCP-compatible AI assistant (e.g., Cursor, VS Code, Claude Desktop).
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@secscan-mcprun a full security scan on this project with high severity threshold"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
secscan-mcp
A portable MCP server for security scanning — works with any AI coding assistant that supports the Model Context Protocol: Cursor, VS Code, Claude Desktop, Windsurf, Zed, Continue, and more.
Scan codebases for hardcoded secrets, SAST issues, vulnerable dependencies, and IaC misconfigurations — one install, one normalized report format.
The built-in custom scanner works with no extra tools. Install optional CLIs for broader coverage (below).
Quick start
Requires Python 3.11+. If pip install secscan-mcp says "No matching distribution found", your default python3 is likely too old — use python3.11 -m pip install secscan-mcp or install Python 3.11+ first.
1. Install from PyPI:
pip install secscan-mcp
# or explicitly:
python3.11 -m pip install secscan-mcpOr run without installing (requires uv):
uvx secscan-mcpFor MCP config with uvx, use "command": "uvx" and "args": ["secscan-mcp"] — see setup guide.
git clone https://github.com/openjkai/secscan_mcp.git
cd secscan_mcp && pip install .2. Add to your IDE — pick your client:
IDE / client | Config file | Guide |
Cursor |
| |
VS Code |
| |
Claude Desktop | OS-specific (see guide) | |
Claude Code |
| |
Windsurf |
| |
Others | — |
Minimal config (works in Cursor, Claude Desktop, Windsurf):
{
"mcpServers": {
"secscan": {
"command": "uvx",
"args": ["secscan-mcp"]
}
}
}If you installed with pip install secscan-mcp, you can use "command": "secscan-mcp" instead.
3. Verify — ask your agent: "Call list_available_scanners and scan_secrets on this project."
Related MCP server: ai-scanner-mcp
MCP tools
Tool | Purpose |
| Which engines are installed on this machine |
| Hardcoded credentials and secrets (optionally scan git commit history) |
| SAST (semgrep, bandit) |
| Vulnerable packages (osv-scanner) |
| IaC misconfigurations (checkov) |
| All available scanners, one unified report |
| Remediation hints for a |
Most scan tools accept path (directory to scan) and optional severity_threshold (critical, high, medium, low, info).
scan_secrets also accepts include_git_history (boolean). When true, scans past git commits for secrets removed from the working tree but still present in history — no extra tools required beyond git. scan_all accepts include_git_history too.
Suppressing false positives
Silence known-good findings without changing scanner behavior. Both mechanisms apply to every engine, and each report includes a suppressed count so nothing is hidden silently.
.secscanignore at the project root — gitignore-style path globs:
# ignore vendored code and test fixtures
vendor/
tests/fixtures/
*.min.jsInline # nosecscan on the offending source line — suppress all rules there, or scope to specific rule IDs:
API_TOKEN = get_token() # real code, no marker
LEGACY_KEY = "AKIA..." # nosecscan
DEMO_JWT = "eyJ..." # nosecscan: hardcoded-jwtOptional scanners
Install any of these to extend coverage. Missing CLIs are skipped — the server still runs.
Engine | Category | Install (example) |
gitleaks | secrets |
|
semgrep | SAST |
|
bandit | SAST (Python) |
|
osv-scanner | dependencies |
|
checkov | IaC |
|
After installing, run list_available_scanners again to confirm.
Example prompts
"Call
list_available_scannersand tell me what's installed.""Run
scan_secretswith include_git_history on this repo — check if any secrets were ever committed.""Run
scan_allwith severity_threshold high and summarize the findings.""Explain the rule
internal-api-key.""Add a
.secscanignorefor thetests/fixturesdirectory and re-run the scan."
Configuration
Environment variables (optional):
Variable | Default | Description |
|
| Per-engine scan timeout |
|
| Max findings per report |
|
| Max commits scanned in git history mode |
Pass via MCP config env block — see setup guide.
Development
make install-dev # editable install + dev tools
make check # lint + typecheck + testSee docs/CONTRIBUTING.md and PLAN.md.
License
MIT
Available Tools
7 toolsexplain_findingA
Return remediation guidance for a finding rule_id (from any scan result). Recognizes built-in secret rules, bandit test IDs (B###), semgrep rule paths, gitleaks rule names, checkov policies (CKV_*), and dependency advisories (CVE/GHSA/PYSEC), with documentation links where available.
| Name | Required | Description | Default |
|---|---|---|---|
| rule_id | Yes | The rule_id field from a finding in a scan report. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It reveals supported rule ID formats and that documentation links are included. Does not mention side effects, but as a guidance tool, destructive behavior is unlikely.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no redundant words. Every sentence provides essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema and no annotations, the description sufficiently explains what input is needed, what output to expect (remediation guidance with links), and the range of supported rule IDs. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with param description. Description adds meaning by specifying the accepted rule_id formats (built-in secret rules, bandit, semgrep, etc.) and that it works 'from any scan result', providing useful context beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action ('return remediation guidance') and the resource ('finding rule_id'). It also distinguishes from sibling tool 'list_available_scanners' by specifying it operates on rule_ids from any scan result.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Indicates when to use (for rule_id from scan results) and lists supported rule ID formats. Does not explicitly state when not to use or provide alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_available_scannersA
List all supported scanners and whether each engine CLI is installed. Call this before scanning to know which tools will run.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the core behavior (listing scanners and installation status). However, with no annotations and no output schema, it could additionally specify the response format or any prerequisites, though for a simple listing tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with no superfluous words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless tool, the description fully covers what it does and when to use it, leaving no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameters (coverage 100%), so no parameter details are needed. The description adds value by explaining the tool's function, which is the baseline for no-param tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List all supported scanners and whether each engine CLI is installed.' This directly distinguishes it from sibling tools like scan_code or scan_all, which perform actual scanning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises 'Call this before scanning to know which tools will run,' providing clear when-to-use context and implicitly differentiating from scanning tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_allA
Run every installed scanner (secrets, SAST, dependencies, IaC) and return one unified, deduplicated report. Set include_git_history=true to also scan git commit history for leaked secrets — recommended before push/PR.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute or relative path to the project directory to scan. | |
| severity_threshold | No | Minimum severity to include in results (default: info — all severities). | |
| include_git_history | No | Also scan git commit history for secrets, not just current files. Finds secrets deleted from source but still in old commits. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions running scanners and producing a unified deduplicated report, and describes the include_git_history behavior. However, it does not disclose potential side effects (e.g., whether it modifies files), auth requirements, rate limits, or behavior if scanners are missing, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences (34 words), front-loading the main purpose and following with specific advice. Every sentence is meaningful with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain return format more fully. It mentions 'one unified, deduplicated report' but lacks details on structure, severity filtering, or error cases. With sibling tools available, not referencing them for comparison reduces completeness. Overall adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by advising when to set include_git_history=true ('recommended before push/PR'), which goes beyond what the schema provides. This improves guidance for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs every installed scanner (secrets, SAST, dependencies, IaC) and returns one unified deduplicated report. It distinguishes itself from sibling single-scanner tools like scan_secrets or scan_code, making the purpose specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description recommends using include_git_history=true before push/PR, providing clear context for when to enable that parameter. However, it does not explicitly contrast with sibling tools or state when not to use this tool, limiting guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_codeA
Static analysis (SAST) for code vulnerabilities and unsafe patterns. Uses semgrep and bandit when installed; skips missing engines.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute or relative path to the project directory to scan. | |
| severity_threshold | No | Minimum severity to include in results (default: info — all severities). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that semgrep and bandit are used conditionally and missing engines are skipped. However, it does not mention read-only nature, authentication needs, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet the description does not explain what the tool returns (e.g., list of findings, format). This is a significant gap for a scan tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add meaning beyond what the schema already provides for the two parameters; it only mentions engines but not parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs static analysis (SAST) for vulnerabilities and unsafe patterns, and names specific engines (semgrep, bandit). This purpose is distinct from sibling tools like scan_secrets or scan_dependencies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for code-level vulnerabilities but does not explicitly state when to use this tool versus alternatives like scan_secrets or scan_dependencies. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_dependenciesA
Scan lockfiles and manifests for known vulnerable dependencies (SCA). Uses osv-scanner when installed.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute or relative path to the project directory to scan. | |
| severity_threshold | No | Minimum severity to include in results (default: info — all severities). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states it scans lockfiles/manifests and uses osv-scanner, but it does not disclose behavioral traits such as file modification, network access needs, or if it requires the scanner to be installed. It is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy: first states purpose and scope, second adds implementation detail. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description could clarify return values. It does not explain how results are presented or how this tool fits with sibling scanners. Missing integration guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds no extra meaning beyond the schema definitions for path and severity_threshold. It mentions SCA but does not elaborate parameter usage or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scans lockfiles and manifests for vulnerable dependencies, using SCA, and specifies the tool it uses (osv-scanner). This distinguishes it from siblings like scan_secrets or scan_code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the use of osv-scanner but does not provide explicit guidance on when to use this tool versus alternatives like scan_all or when not to use it. The usage context is implied rather than clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_iacB
Scan Terraform, CloudFormation, Kubernetes, and other IaC for misconfigurations. Uses checkov when installed.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute or relative path to the project directory to scan. | |
| severity_threshold | No | Minimum severity to include in results (default: info — all severities). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It mentions using checkov and dependency status, but does not state safety (e.g., read-only) or side effects. Missing details on failure mode if checkov not installed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant words. Essential information presented efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description does not explain return format or what the scan results look like. Also lacks behavior when checkov is not installed. Incomplete for a tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions, achieving 100% coverage. Description adds context about checkov but no additional parameter meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool scans IaC (Terraform, CloudFormation, Kubernetes) for misconfigurations, using a specific verb and resource. It distinguishes from siblings by specifying the domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage when dealing with IaC files, but no explicit guidance on when to use vs alternatives (e.g., scan_secrets for secrets). Does not mention when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_secretsA
Detect hardcoded secrets and credentials in a directory. Runs the built-in custom scanner (no extra tools). When include_git_history is true, also scans past git commits for secrets removed from the working tree but still in history — recommended before push/PR. Uses git_history (built-in) and gitleaks (when installed).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute or relative path to the project directory to scan. | |
| severity_threshold | No | Minimum severity to include in results (default: info — all severities). | |
| include_git_history | No | Scan git commit history, not just current files. Finds secrets deleted from source but still in old commits. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that scanning uses built-in git_history or gitleaks when installed, and mentions scanning of past commits. However, it does not cover other behavioral aspects like performance impact or permissions required, which would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, each sentence adding specific information without fluff. The main action is front-loaded, and the structure is clear and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a scanner with no output schema, the description adequately covers the tool's behavior, including git history scanning and the use of built-in tools. It is complete enough for an agent to understand when and how to invoke it, though it could mention the default severity behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context for include_git_history ('also scans past git commits... recommended before push/PR') and clarifies that the scanner is built-in, adding value beyond the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear verb+resource: 'Detect hardcoded secrets and credentials in a directory.' It also specifies the built-in scanner and distinguishes git history scanning, making the tool's purpose specific and differentiating from siblings like scan_code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance for include_git_history: 'recommended before push/PR.' It implies when to use the tool for secrets detection, but does not explicitly contrast with sibling tools like scan_code or scan_dependencies, leaving some ambiguity about alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a clearly distinct purpose: scan_secrets, scan_code, scan_dependencies, and scan_iac target different security domains; scan_all is a meta-runner; list_available_scanners and explain_finding serve informational and post-scan roles. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern with a logical prefix: scan_ for scanning actions, list_ for listing, and explain_ for explanation. The naming is predictable and coherent.
Seven tools is an ideal scope for a security scanning MCP server. It covers the major scan types plus utilities for listing available scanners and explaining findings, without unnecessary bloat or missing essentials.
The tool set covers the full lifecycle of security scanning: pre-scan discovery (list_available_scanners), individual scans for all major domains (secrets, code, dependencies, IaC), a combined scan (scan_all), and post-scan remediation (explain_finding). No obvious gaps for typical use cases.
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