MCP server

Spark - AI Assets Marketplace

io.github.entire-vc/spark

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Search and fetch AI agents, skills, prompts and MCP connectors from the Spark marketplace.

Website Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

6

Token cost

About 2,234 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http spark https://spark.entire.vc/mcp/

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.spark]
url = "https://spark.entire.vc/mcp/"

Gemini CLI

{"mcpServers":{"spark":{"httpUrl":"https://spark.entire.vc/mcp/"}}}

Cursor

{"mcpServers":{"spark":{"url":"https://spark.entire.vc/mcp/"}}}

VS Code

{"servers":{"spark":{"type":"http","url":"https://spark.entire.vc/mcp/"}}}

Antigravity

agy mcp add spark https://spark.entire.vc/mcp/

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"spark","server_url":"https://spark.entire.vc/mcp/","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"spark","server_url":"https://spark.entire.vc/mcp/"}

Tools

• get_asset ~215 tokens
  Get full details of a Spark asset by its slug — description, metadata, outcome reports, bundled files and the URL on spark.entire.vc. For when a known slug needs inspection before acquisition. Returns Markdown details, which may include embedded content; get_asset_content obtains the raw content an
• get_asset_content ~294 tokens
  Get the raw content of a Spark asset (prompt text, skill instructions, agent config) — the actual text to apply, not just a description of it. For when a known asset's content is needed for application; get_asset provides details without acquisition. Each successful fetch records a download/acquisi
• list_categories ~176 tokens
  List available categories (domains and AI tags) in the Spark marketplace. For when domain filter values or taxonomy are needed; search_assets returns assets rather than categories. Takes no parameters. Returns Markdown lists of AI tag names/slugs and domain names/slugs grouped by parent category; d
• list_popular ~240 tokens
  List the most popular Spark assets by download count, optionally filtered by type. For when browsing without a text query; search_assets finds text matches. Returns numbered summaries with outcomes, price, tags and URLs, or 'No assets found.' Downloads measure acquisitions, not successful applicati
• report_outcome ~802 tokens
  Records the result of applying a fetched Spark asset: applied as is, changed, broke, or not applicable. For when the outcome is known and an application_id from get_asset_content is available, rather than a star rating. Mismatched user/session receipts are rejected; asset owners cannot report on the
• search_assets ~507 tokens
  Search the Spark AI assets marketplace for agents, skills, prompts, prompt chains, MCP connectors and bundles. For when a text query is available but the slug is not known; get_asset describes a known slug. Returns numbered summaries with type, downloads, outcomes, price, tags and URL, or a no-resu

Browse

• GitHub tools
• SEO
• Converting to Markdown
• GitHub and code hosting

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