"Secret scanning and credential detection tools" matching MCP servers:

Machine-readable detection lookups for SIEM enrichment and AI agents. Query 800+ LOLBAS and GTFOBins binaries plus process parent-child baselines — get risk levels, abuse categories, and MITRE ATT\&CK mappings without embedding data in prompts.

Enables scanning diffs or code blobs for leaked secrets, returning a verdict with severity and masked findings, all processed locally with no data sent externally.

Enables agents to request an API key or other secret from the user without the value passing through chat or tool arguments/results, storing it directly to .env, the OS keychain, or 1Password. The agent receives only metadata indicating whether storage succeeded.

Enables an MCP client to write, validate, run, explain, and tune Snort 3 detections against packet captures on disk offline, with every change verified by real engine runs and recorded in exportable case reports.

Local STDIO MCP server for object-detection annotation workflows. Manages datasets, categories, images, bounding boxes, and exports in JSONL format without modifying source images.

Enables secure credential storage for AI agents by encrypting secrets and providing agent-invisible references, ensuring sensitive data never leaks to the model.

Enables AI assistants to write .env files with secrets stored locally, allowing search by name/description while keeping actual secret values private and never exposed to the AI.

MCP server for one-time secret sharing, enabling AI agents to securely claim and store secrets (e.g., API keys) via claim codes without exposing them in chat transcripts.

An MCP server that enables AI agents to securely add secrets to .env files by prompting the user to input the value through a local masked dialog, ensuring the agent never sees the secret.

An MCP server that scans code for exposed secrets (API keys, tokens, private keys, high-entropy strings) with placeholder-aware allowlisting and fully redacted reports, enabling agents to detect leaks before committing.

Scans files, directories, and environment configurations for exposed secrets, API keys, and credentials, redacting matches and providing allowlist support. Enables natural-language secret detection in projects and CI/CD integration via CLI.

Enables secure delivery of Bitwarden Secrets Manager secrets to approved local files without exposing secret values to the MCP client or model. It provides metadata-only secret discovery and atomic file writes for single secrets or raw env files.

Enables offline, deterministic verification of credential retirement settlements from explicit receipts, proving that rotations activated new credentials, rejected old ones, and closed without exposing secrets.

Enables scanning staged diffs, files, and raw text for secrets before they are committed, fully offline with masked findings and severity-based gating.

Enables detection of duplicate patient records for a Master Patient Index by scoring record pairs and providing verdicts and reasons, intended for synthetic data only.

A secure MCP server for local API credential management using JSON storage and a read-only default mode. It allows users to list, retrieve, and manage credentials via simple command-line tools and environment-based configuration.

Enables multi-tier AI-detection screening on academic papers by extracting text from .tex and .docx files, splitting into standard sections, and running a pipeline of statistical and LLM-based analysis.

Secure secrets vault MCP server storing credentials in the OS credential manager, exposing tools to set, get, delete, and list secrets without revealing values.

Enables an agent to scan text for leaked credentials locally before it writes or commits it, flagging known key, token, private-key and sensitive-filename patterns with redacted, line-level findings and no network calls. Detection is deliberately specific to avoid false positives that would block unattended agents.

A local-first MCP server that lets AI agents use gated APIs without holding keys, enforcing declarative policies, injecting secrets server-side, and auditing access without content.

AI-powered fraud detection and investigation platform that exposes tools for querying, scoring, and investigating financial applications using LangGraph, MLflow, and SQLite in-memory.

Exposes account risk status from a fraud detection pipeline, returning risk scores, flagged transaction history, and LLM-generated explanations via the get_account_risk_status tool.

Scans projects for hardcoded secrets, unprotected .env files, and console.log leaks to prevent credential exposure.

An MCP server that enables AI-powered fraud detection on financial transactions using rule-based and statistical analysis tools, with sample data and Gradio dashboard.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

MCP server for personal knowledge management providing AI-powered tools for semantic search, audio transcription, image generation, and PPT creation.

Provides five safe tools (calc, search, model_drift, compare_runs, grade_answer) for arithmetic, keyword search, model drift monitoring, eval comparison, and answer grading against sources, all implemented directly from the MCP spec with zero dependencies.

Enables evidence-grounded web design analysis by searching GDWEB references and generating isolated, per-reference DESIGN_INDEX specification documents for LLM-driven frontend development.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Enables extraction of recipes from PDFs or JPG files and conversion into structured HTML, with interactive region selection and OCR via a web GUI.