"Servers Offering MCP Prompts as Prompt Primitives" matching MCP servers:

Enables searching for high-quality AI art prompts from Banana Prompts by tags or keyword queries, with direct links to full prompts and images.

It enables users to search public prompt libraries for complete prompts with example images and source links, list model names and official prices, and request text-model optimization when a search has no match or a rewrite is explicitly requested, all without an account or API key.

A Model Context Protocol implementation for managing and serving AI prompts with a TypeScript-based architecture in a monorepo structure.

Manages AI prompts stored in Notion databases, enabling search, retrieval, and management across multiple prompt collections.

Enables clients to optimize prompt prefix caching by matching longest common token prefixes with a radix trie, eliminating redundant prefill computation and reducing time-to-first-token.

Compresses multi-turn conversation history by stripping verbose boilerplate and filler tokens while preserving critical tool parameters and named entities, deterministically cutting inference costs by 40-60%. Runs as a zero-dependency Python MCP server or importable module, compatible with Claude Desktop, Cursor, and other MCP runtimes.

Enables MCP-compatible clients to deterministically neutralize adversarial prompt injections and jailbreak overrides with zero-dependency, sub-millisecond heuristic analysis.

Enables deterministic detection and neutralization of adversarial prompt injections and override attempts in AI agent workflows via a zero-dependency MCP server, providing structured telemetry and low-latency validation.

Enables autonomous AI agents and MCP-compliant clients to detect and block adversarial prompt injections, jailbreak attempts, system prompt exfiltration, and tool hijacking via a zero-dependency, sub-millisecond heuristic firewall.

A remote MCP server exposing 3 tools via Model Context Protocol: score_prompt (free, grades any LLM prompt A-F on 0-40 scale), optimize_prompt (returns optimized prompt + dimension breakdown, $0.025 USDC), and compare_models (Claude vs GPT-4o head-to-head, $1.25 USDC). Remote HTTP server at /api/mcp.

Facilitates access and management of Langfuse prompts through the Model Context Protocol, enabling prompt discovery, retrieval, and integration within clients like Claude Desktop and Cursor.

Free MCP tools for context engineering audits of AI agents, offering on-demand analysis of system prompts, tool definitions, and context packing.

Exposes TELOS governance primitives—action scoring, receipt verification, Purpose Anchor inspection, audit-chain queries, and CCRS counterfactual replay—as MCP tools, resources, and prompts for any MCP-compatible client.

Protects AI agents from prompt injection and destructive actions while enabling self-improving prompts through a security pipeline.

Intelligent framework-aware context layer for AI-powered WordPress plugin development with WPZylos + WooCommerce support, offering 55 tools, 12 resources, and 9 prompts.

Integrates AI safety analysis, red-teaming, and prompt auditing directly into MCP-compatible clients like Claude Desktop and Cursor IDE, allowing real-time analysis of prompts and detection of jailbreak attempts.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables AI coding agents to automatically lint and auto-fix their generated prompts before running them, helping improve prompt quality, security, and cost efficiency.

Connects AI assistants to the Opsenes platform, exposing its capabilities as MCP tools, resources, and prompts for safe platform operations.

MCP server that exposes fleet-aware KVM primitives for AI agents to control TinyPilot devices, including screen capture, keyboard input, mouse events, and device selection.

Context intelligence for AI coding sessions. 7 MCP tools to score, compare, compress, build, and scan prompts across 9 AI tools. Rule-based, <5ms/prompt, all analysis runs locally.

Enables AI clients to transcribe YouTube links and uploaded audio or video files, then retrieve the resulting transcripts as text, SRT, VTT, or JSON with timestamps and optional speaker labels. Also supports paging through long transcripts, checking upload progress, listing or deleting jobs, and viewing remaining account minutes.

Brazilian foreign trade from MDIC/ComexStat -- exports and imports since 2000 by HS code (SH4/SH6/NCM) and partner country, in USD FOB and kilograms -- plus crop production, supply-and-demand balances, climate readings and commodity forecasts for hubs such as soybean, coffee and beef. 15 read-only tools, remote at https://mcp.kyrodata.com/mcp; official registry com.kyrodata/kyrodata.

An MCP server for querying the FDSN Web Service Event APIs of multiple seismological datacenters and retrieving earthquake information as JSON.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Enables AI agents to make pay-as-you-go AI inference requests through x402 with automatic Solana USDC payments, no API keys or registration, while enforcing configurable spending limits.

Provides a local MCP server that exposes the check_prompt_injection tool to MCP clients, letting agents scan untrusted text (web pages, documents, tool outputs, emails) for prompt injection before passing it to another LLM.

Enables agents to inspect PDF, Microsoft Office, and Apple iWork documents without rendering them, providing page/slide counts, metadata, security signals, structure, and integrity as deterministic JSON via typed tools and batch operations.

MCP server for SrezAI providing web search, page reading, screenshots, and schema-based extraction as native agent tools.

Enables LLM agents to retrieve normalized US-GAAP financial statements from SEC EDGAR—income statement, balance sheet, and cash flow—with point-in-time as-reported figures and per-value SEC source provenance for citation.