"A search for the term 'Prompt'" matching MCP servers:

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A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A FastMCP server for bounded, keyword-driven repository context search, enabling efficient codebase exploration with snippet extraction and focused code block retrieval.

Provides a code search service via MCP, allowing AI clients to perform fast, indexed searches across large codebases using Zoekt, with support for filters like repository, language, and path.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Security scanner for AI agent packages that enables AI agents to audit MCP servers and packages for vulnerabilities, prompt injection, and supply chain attacks.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

Vet ClawHub skills before installing them; detects prompt-injection, exfiltration, and other security issues, outputting a risk score with per-finding evidence.

Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Clones a Git repo into a temp directory so MCP clients can search and read files from another repo for context.

Enables AI agents to perform semantic code search across entire codebases using natural language queries. Provides fast indexing and ranked search results with line numbers and file paths through the Seroost search engine.

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Enables AI-assisted X++ development for Dynamics 365 Finance and Operations by pre-indexing the entire codebase and providing 54 specialized tools for metadata lookup, code generation, and best practice validation.