"Search functionality without API key requirement" matching MCP servers:

Stop letting your agent guess at APIs. Ask the code you actually installed. installed-api is a Claude Code plugin (an MCP server, Python standard library only) that answers "what's the signature of X?", "does Y take that argument?" and "which version do we have?" from the packages installed in this project: your .venv, your node_modules.

Enables SDK and MCP clients to perform repository code search and retrieval, inspect current source and related evidence, and optionally use semantic search, reranking, and web sources while keeping the calling agent in control.

Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.

Semantic + lexical code search as an MCP server. Agents query in natural language and get back ranked file:line ranges to read precisely.

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.

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.

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

Provides the real exported API surface and type signatures of any npm package, extracted from its published TypeScript declarations, enabling AI coding agents to use functions accurately and avoid inventing nonexistent APIs.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

Enables AI coding agents to perform fast regex/text and structural AST searches across codebases, find symbols, list files, and safely preview or apply refactors. It unifies ripgrep and ast-grep with pagination, gitignore-aware defaults, and fallback engines for zero-setup code search.

Provides semantic code search over codebases using local embeddings with natural language queries. Supports hybrid search, file watching, and respects .gitignore.

Tracks latest versions and breaking changes for popular SDKs, enabling agents to check version updates and potential breaking changes efficiently.

MCP server for DayZ Enforce Script that gives AI coding assistants deep knowledge of the DayZ scripting API with semantic search, code validation, class hierarchy, and reverse call graphs.

Semantic code search for Claude Code, enabling natural language codebase indexing and search using AI embeddings.

Enables scanning repositories for hardcoded service URLs and clients, and building service-to-service API dependency maps.

Enables intelligent code analysis and search across repositories using the CodeRank algorithm (inspired by PageRank) to identify critical modules, trace dependencies, find code hotspots, and perform context-aware keyword searches with importance-ranked results.

Enables scanning code for deprecated annotations and comments, building a deprecation catalog, and tracking deprecated endpoints and features.

Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.

Scan-as-a-Service for MCP servers. Wraps the compuute-scan static security scanner with HTTP and MCP endpoints to analyze public GitHub repos for MCP-specific vulnerabilities.

Enables AI coding agents to perform semantic code search locally, finding code by meaning rather than exact keywords.

Enables token-bounded, read-only hybrid code search across local repositories by fusing literal matches with AST symbol relations to return high-signal snippets, line ranges, and call metadata.

Enables cross-repository code search over a local mirror of a self-hosted Gitea or Forgejo instance, covering file contents, file paths, and commit messages across all repositories and branches. It also lets users read a single file from the mirror and list mirrored repositories, all without network access during search or read.

Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.

Enables read-only code search in a specified local directory and public web search through the user's own Devin session, with login handled only in the terminal.

Exposes a running VS Code instance to AI agents via MCP, enabling file operations, LSP diagnostics, terminal commands, Git workflows, and refactoring.

Indexes Kotlin/Native platform klibs to enable fast symbol lookup for iOS APIs. Supports querying classes, members, and platform constants via MCP tools for Kotlin Multiplatform development.

Helps LLMs write correct Ghidra scripts by providing API call-flows extracted from Ghidra's source code.

MCP server for angr binary analysis API workflow retrieval. Extracts real API usage patterns from angr's source code and angr-doc examples, then indexes them with semantic search so LLMs can query correct API call sequences.