"Bash shell scripting and command line resources" matching MCP servers:

Provides semantic search over ScriptingApp documentation by converting Markdown/MDX files into a LlamaIndex vector store. Supports multi-language indexing and enables natural language queries against technical documentation through MCP tools.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables AI assistants to query a company's inventoried productivity tools and subscriptions through MCP, answering questions about what is paid for, which tools overlap in function, and what renews next quarter. Exposes read-only tools such as list_stack, get_tool_context, find_overlap, and stack_summary over the local inventory file as typed context packets.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Indexes git history, shell commands with exit codes, project docs, and opt-in assistant transcripts into a local SQLite database, then serves ranked, token-budgeted context back over MCP. Uniquely links a failed shell command to the commit that fixed it, so agents can recall what was already tried and what worked.

Enables agents to find lines in local text files by meaning rather than exact keywords, judging each nonblank line against a natural-language intent and returning scores for every line. It complements lexical search by running locally over stdio and calling a hosted model for the semantic comparison.

Your smartest line to any API. Hebline routes your agents to the best service at the best price — including free alternatives.

Enables coding agents to search locally indexed repositories with hybrid semantic and lexical retrieval, returning exact source citations with file paths and line ranges.

A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.

Integrates Dify's external knowledge base API with the Model Context Protocol to enable AI agents to retrieve and query relevant information. It supports relevance scoring, metadata filtering, and flexible configuration through environment variables or command-line arguments.

Enables XTend developers and agents to search and retrieve canonical XTend documentation, recipes, and kit resources through read-only MCP tools, resources, and prompts served over stateless HTTP.

Enables MCP clients to query previously analyzed GitHub repositories for architecture analysis, code review findings, and single-turn code Q&A with verifiable file and line references.

A command-line tool that transforms any OpenAPI service into a Model Context Protocol (MCP) server, enabling seamless integration with AI agents and tools that support the MCP specification.

Provides ranked full-text search over Obsidian vaults using SQLite FTS5, BM25 scoring, and multilingual stemming, adding a vault_fts_search tool to find relevant notes beyond exact line matches.

A tiny RAG-lite retrieval engine that indexes files on disk and provides semantic search via MCP, returning relevant text chunks (file, line, score) without generating answers.

Enables semantic and keyword search of Ceph documentation with version-aware, component-scoped indices, supporting command lookup and code example retrieval.