"Creating an application" matching MCP servers:

The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Multi-source academic paper search, citation graph exploration, and PDF download as an MCP server, designed for LLM agents doing research.

An MCP server for the iNavi Maps API that gives AI assistants iNavi Maps API specifications and ready-to-use HTML templates for interactive map visualizations (geocoding, POI search, route planning).

Turns team chat (Slack, Discord, MS Teams, Mattermost) into a living knowledge base - a typed knowledge graph plus auto-generated wiki - exposed to AI agents through a 28-tool MCP server with semantic search, expert finding, and decision tracing.

Enables AI agents to send emails and manage tasks in Microsoft To Do with scoped, low-risk access to Microsoft Graph.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

Pay-per-call USDC payment proxy for AI agents. Issue scoped Pay Tokens with hard spending caps and auto-journal every charge to freee / Money Forward / QuickBooks.

Enables users to draw GIS geometry on an interactive map and get clean, validated GeoJSON to hand off to other GIS MCP servers such as FEMA flood screening and USGS hydrography.

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.

Fetches documents by URL, DOI, ISBN, PMID or PMCID, and reports a block as a block, never as an empty success.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

An MCP server that reads a file's embedded C2PA Content Credential to report whether it declares AI generation or a real-world capture, and checks whether that declaration's signature still verifies against the file's current bytes.

A universal MCP aggregator toolkit that connects AI agents to multiple MCP servers through a single unified configuration. Features ready-made templates, cross-repo prompt workflows, and an npm package for zero-config installation.

An MCP server that protects AI agents and RAG systems from adversarial poisoning attacks like prompt injection, steganography, and data anomalies through multi-layer sanitization, entropy-based detection, and consensus verification.

Generate professional AI-powered presentations from a topic, raw text, or document file. Export to PPTX, PDF, image, or shareable link.

An MCP front-end for AnB. The tool surface is "use-don't-reveal": no tool returns a plaintext secret. Reveal paths require a TTY the server doesn't have, so the no-reveal guarantee is structural, not prompt-based — it holds even against a prompt-injected agent. Runs as a dedicated, narrowly-scoped AnB identity; exec is default-deny (only allowlist rules tagged scope=mcp run); command output

Enables real-time user intervention for MCP agents through a web UI, allowing users to review context and provide feedback when AI agents drift from intent, keeping them on track.

Bridges the editing capabilities of an already-open DingTalk document in the browser to any MCP host via standard stdio, forwarding tools to the page's internal MCP server over a local WebSocket. Supports read/write operations through suggested edits, pairing-based security, and zero runtime dependencies.