"Pocket Casts" matching MCP servers:

🔗 Model Context Protocol (MCP) Server for retrieving saved articles from Pocket API and loading them into Claude

AgentSearch web search (and optional page extract) via MCP stdio. Direct local API or Pocket portal.

Lets AI assistants search every Pokémon TCG Pocket card by name, type, rarity, set, evolution stage, ability effect and attack, in six languages, with typo tolerance and semantic search.

MCP server for ai-divination-skills that provides tools for tarot draws, I Ching casts, Xiao Liu Ren casts, and Bazi chart generation, returning auditable JSON results for AI interpretation.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables LLMs to read a user-owned, local-first memory store kept in a portable folder (USB, SSD or laptop), with per-profile permissions limiting what each client can see and access cut off when the pocket is locked or unplugged. Also lets models propose new memories for the user to review and approve, keeping provenance and keeping canonical memory free of direct model writes.

Enables AI agents to search, describe, and call paid data services from the Pocket Network agentic marketplace, paying per request in USDC via x402.

Enables bounded administration of Pocket ID, focusing on OIDC client management and read-only identity inventory, with secure handling of API keys and client secrets.

Persistent memory storage using SQLite for AI agents to store, search, update, and manage contextual memory via the Model Context Protocol.

Enables an AI assistant to keep every conversation verbatim in a local SQLite store and recall the most relevant past turns on demand, using hybrid keyword and embedding search plus time-awareness. Results are packed into a small token budget (2k–8k tokens) so long histories fit modest context windows, with secrets masked before storage.

Turn your AI coding agent into a producer of interactive, narrated walkthroughs — code, whiteboard, and 3D casts, each a single self-contained HTML file that opens in any browser. Runs locally over npx.

Enables coding agents to query a local OTLP trace collector: list recent traces, inspect span trees and critical paths, flag SQL N+1 loops, surface gen_ai metrics, and diagnose slow traces with a local OpenAI-compatible model.

Enables an AI assistant to control a Sonicake Pocket Master guitar processor over USB MIDI by describing tones in plain words — selecting amp/cab/effect models, setting parameters, reordering the signal chain, and saving, renaming, backing up or restoring presets. It also provides offline tools for inspecting firmware and rebuilding it with a translated UI, such as Russian.

One todo list every AI coding agent can write to — Claude Code, Codex, Cursor — scoped per project, local-first, self-hostable.

A deterministic video rendering engine that enables AI agents to create programmable, reproducible videos via MCP protocol.

A local MCP server for interacting with a network lab, supporting read-only and configuration tools for devices like Arista EOS switches.

Open-source skills that empower any AI agent (Claude, Cursor, Codex, Hermes, etc.) to generate end-to-end marketing campaigns — UGC videos, ad videos, product photography and more. From a product photo and a brief it casts AI actors, picks the best models, and edits finished assets of any length with consistent actor and product. It also researches competitors, publishes, and reviews performance.

Enables querying a dataset of Japanese advertising-law enforcement actions, offering search, retrieval, recent listings, and statistical summaries so models can cite real orders rather than inventing them.

Enables controlling Cisco Packet Tracer through its native PTMP/IPC interface to create devices and links, configure IOS and PC addresses, run real ping tests, save .pkt files, and export topology as PNG.

Enables MCP agents to inspect and precisely edit a paired browser editor project through local stdio, with batch commands, previews, exports, validation, and guarded undo/redo while keeping changes hand-editable.

Enables AI assistants and coding agents to query a normalized multi-cloud catalog for compute, database, serverless, and AI-model token pricing, estimate full-stack workload architecture costs, and look up data-center availability and compliance pointers directly within their workflows.

Enables automation of Cisco Packet Tracer simulations by placing devices, connecting links, and generating IOS configurations via MCP, ideal for network coursework and demonstrations.

Enables natural-language construction and configuration of Cisco Packet Tracer topologies, including devices, cabling, IOS commands, VLANs, routing protocols, and network reproduction from diagrams.

Enables control of Cisco Packet Tracer 9.0 via natural language, allowing creation of network topologies, device configuration, and simulation launches through an MCP interface.

Enables MCP-compatible clients to plan, validate, generate, and deploy complete network topologies from natural-language instructions, including live deployment to a running network simulator and export to configuration or script files.

Connects Claude with Cisco Packet Tracer 9.x to control network topologies, configure devices with IOS commands, and run diagnostics via natural language.

Enables external control of Cisco Packet Tracer 9.0 through MCP, allowing users to create network topologies, configure routers, and launch simulations from MCP clients.

Enables AI assistants and security analysts to inspect PCAP/PCAPNG captures through MCP tools or REST endpoints, reassembling TCP/UDP streams, extracting payload artifacts, detecting CTF flags, credential leaks and network anomalies, and generating formal PDF or Markdown forensic reports. Every finding is bound to exact frame numbers, timestamps and endpoints with SHA-256 deduplicated evidence provenance.

Enables AI agents to control Cisco Packet Tracer in real time, allowing natural language-driven creation and configuration of network topologies.

Enables AI agents to plan, create, and control Cisco Packet Tracer network topologies in real time, including deploying devices and cabling, configuring IPs and IOS CLI, and querying or clearing topologies through an HTTP bridge.