"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.

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

Scans code for exposed secrets, API keys, tokens, and credentials across 69 patterns covering cloud services, AI platforms, payment providers, authentication services, and databases.

Credential Manager - MCP server providing AI-powered tools and automation by MEOK AI Labs

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.

Enables security teams to determine which ATT&CK techniques lose detection coverage when telemetry sources are removed, by computing set differences over a Sanity content graph and consulting a knowledge base via two Context MCP endpoints.

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.

Bias Detection - MCP server providing AI-powered tools and automation by MEOK AI Labs

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.

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 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.

Local, encrypted password vault with AES-256-GCM and PBKDF2, exposing MCP tools for secure credential management, password generation, and search.

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.

MCP server for end-to-end encrypted secret storage and retrieval, enabling LLM agents to fetch secrets by name via one-time URLs while keeping plaintext out of model context and logs.

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

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

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

Enables static analysis and code smell detection by connecting to an external analysis API.

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.