Spark - AI Assets Marketplace

Official6 toolsLive

by entire-vc · TypeScript

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

io.github.entire-vc/spark (MCP Server)

This MCP server, io.github.entire-vc/spark, provides the ability to search and fetch AI agents, skills, prompts, and MCP connectors from the Spark marketplace. The server is described as focused on retrieving content associated with Spark resources rather than generating new content.

🛠️ Key Features

Search Spark marketplace content
Fetch AI agents
Fetch skills
Fetch prompts
Fetch MCP connectors

🚀 Use Cases

Locate AI agents and skills available in the Spark marketplace
Retrieve prompt content from the marketplace
Find MCP connectors listed in Spark for integration

⚡ Developer Benefits

Centralized access to Spark marketplace resources (agents, skills, prompts, connectors)
Supports workflows that require discovering and importing existing marketplace items

⚠️ Limitations

No additional capabilities, tooling, or configuration details are provided in the available data.

Topics

ai-toolschatgptclaudeentire-vcmcpmodel-context-protocolnpmworkflowagent-catalog

Captured live from the server via tools/list.

search_assets

Search the Spark AI assets marketplace for agents, skills, prompts, prompt chains, MCP connectors and bundles. Call this first when you need to find an asset for a task and don't already have its slug — use get_asset/get_asset_content once you know the slug. Returns a numbered list of short summaries; use get_asset for full details on a specific result.

Parameters6

query	string	required	Search text (matches title and description)
job	any	optional	Job/task the agent is trying to accomplish. Enables job-based relevance ranking (e.g. 'review Python code', 'generate marketing copy', 'analyze data'). Recommended for agent use.
type	any	optional	Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle)
domain	any	optional	Filter by domain slug (e.g. 'development', 'marketing')
sort	string	optional	Sort order: combo, popular, newest, rating. 'combo' = combined quality+ratings+agent outcomes score (default, recommended).
limit	integer	optional	Number of results (1-50, default 10)

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search text (matches title and description)"
    },
    "job": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Job/task the agent is trying to accomplish. Enables job-based relevance ranking (e.g. 'review Python code', 'generate marketing copy', 'analyze data'). Recommended for agent use."
    },
    "type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle)"
    },
    "domain": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Filter by domain slug (e.g. 'development', 'marketing')"
    },
    "sort": {
      "default": "combo",
      "type": "string",
      "description": "Sort order: combo, popular, newest, rating. 'combo' = combined quality+ratings+agent outcomes score (default, recommended)."
    },
    "limit": {
      "default": 10,
      "type": "integer",
      "description": "Number of results (1-50, default 10)"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}

get_asset

Get full details of a Spark asset by its slug — description, metadata, outcome reports, bundled files and the URL on spark.entire.vc. Call this once you have a slug (from search_assets, list_popular, or a link) and want the full picture before deciding to use it. It does NOT return the actual prompt/skill/agent content to apply — use get_asset_content for that.

Parameters1

slug

string

required

Asset slug (e.g. 'vb-seo-expert', 'vb-python-expert')

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Asset slug (e.g. 'vb-seo-expert', 'vb-python-expert')"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

get_asset_content

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. Call this once you've picked a slug (via search_assets/get_asset) and are ready to use the asset. Unlike search_assets/get_asset, this counts as a download/acquisition event, and each call may return different content if the asset was updated. For paid assets, authentication is required — add your Spark API key (X-API-Key header) or a Bearer token to your MCP client configuration. The response ends with an `application_id`; pass it to report_outcome once you know whether the asset worked.

Parameters1

slug

string

required

Asset slug

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Asset slug"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

report_outcome

Report what happened when you applied an asset you fetched with get_asset_content. Call it once you know: applied as is, applied with changes, broke, or not applicable. The next agent choosing this asset reads the outcomes in search results. Reports made with an API key count; anonymous ones are stored as unverified. Calling again with the same application_id updates your report. Fields `task`, `note`, `changed_what`, `failed_at`, `expected`, `got` are shown to the asset's author. Do not include client data, private paths, keys, emails or URLs with tokens. Your identity is never shown to the author. Example: report_outcome(application_id='<from get_asset_content>', result='applied_with_changes', task='add a rate limiter to the API', changed_what='swapped the fixed window for a token bucket').

Parameters9

application_id	string	required	The application_id printed at the end of get_asset_content.
result	string	required	applied_as_is: applied without edits, task solved. applied_with_changes: had to edit it, then solved (requires changed_what). broke: tried to apply and it failed (requires failed_at). not_applicable: read it and did not apply, it does something else (requires expected and got).
task	string	required	What you were trying to do, one phrase (≤ 200).
changed_what	any	optional	applied_with_changes: what you changed (≤ 200).
failed_at	any	optional	broke: the step, tool or command that failed, and the error class (≤ 200).
expected	any	optional	not_applicable: what you were looking for (≤ 200).
got	any	optional	not_applicable: what it actually does (≤ 200).
note	any	optional	Anything else worth knowing (≤ 300).
model	any	optional	The model you run on, if you know it. Shown, never ranked.

Raw schema

{
  "type": "object",
  "properties": {
    "application_id": {
      "description": "The application_id printed at the end of get_asset_content.",
      "type": "string"
    },
    "result": {
      "description": "applied_as_is: applied without edits, task solved. applied_with_changes: had to edit it, then solved (requires changed_what). broke: tried to apply and it failed (requires failed_at). not_applicable: read it and did not apply, it does something else (requires expected and got).",
      "enum": [
        "applied_as_is",
        "applied_with_changes",
        "broke",
        "not_applicable"
      ],
      "type": "string"
    },
    "task": {
      "description": "What you were trying to do, one phrase (≤ 200).",
      "type": "string"
    },
    "changed_what": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "applied_with_changes: what you changed (≤ 200)."
    },
    "failed_at": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "broke: the step, tool or command that failed, and the error class (≤ 200)."
    },
    "expected": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "not_applicable: what you were looking for (≤ 200)."
    },
    "got": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "not_applicable: what it actually does (≤ 200)."
    },
    "note": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Anything else worth knowing (≤ 300)."
    },
    "model": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "The model you run on, if you know it. Shown, never ranked."
    }
  },
  "required": [
    "application_id",
    "result",
    "task"
  ],
  "additionalProperties": false
}

list_popular

List the most popular Spark assets by download count, optionally filtered by type. Use this to browse what's trending when you don't have a specific search term — for a targeted lookup, use search_assets instead.

Parameters2

type	any	optional	Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle)
limit	integer	optional	Number of results (1-20, default 10)

Raw schema

{
  "type": "object",
  "properties": {
    "type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle)"
    },
    "limit": {
      "default": 10,
      "type": "integer",
      "description": "Number of results (1-20, default 10)"
    }
  },
  "additionalProperties": false
}

list_categories

List available categories (domains and AI tags) in the Spark marketplace. Call this to discover valid values for search_assets' `domain` filter, or to browse the catalog's taxonomy before searching. Example: list_categories()

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

README.md4 KBView on GitHub

Spark MCP

Smithery

MCP server for Spark — your AI toolbox for real work. Search and discover agents, skills, prompts, bundles, and MCP connectors.

Quick Start

bash

npx evc-spark-mcp

That's it. No API key needed.

Setup

Claude Code

bash

claude mcp add spark -- npx -y evc-spark-mcp

Claude Desktop

Add to claude_desktop_config.json:

json

{
  "mcpServers": {
    "spark": {
      "command": "npx",
      "args": ["-y", "evc-spark-mcp"]
    }
  }
}

Cursor

Add to Cursor MCP settings:

json

{
  "mcpServers": {
    "spark": {
      "command": "npx",
      "args": ["-y", "evc-spark-mcp"]
    }
  }
}

OpenClaw

json

{
  "mcpServers": {
    "spark": {
      "command": "npx",
      "args": ["-y", "evc-spark-mcp"]
    }
  }
}

ChatGPT (via MCP bridge)

Any MCP-compatible client works — just point it at npx evc-spark-mcp.

Tools

Tool	Description
`search_assets`	Search the Spark catalog by query, type, and domain
`get_asset`	Get full details of an asset by slug
`get_asset_content`	Get raw prompt/skill content (best for prompts and skills)
`list_popular`	List most popular assets by download count
`list_categories`	List available domains and AI tags for filtering
`get_api_key_info`	Check your API key status and daily usage
`report_outcome`	Report what happened when you applied fetched content: applied as is, applied with changes, broke, or not applicable

Resources

URI Pattern	Description
`spark://assets/{slug}`	Asset content as markdown
`spark://catalog/{type}`	Asset list by type (agent, skill, prompt, etc.)

What's in the Catalog

Spark is a marketplace of AI workflow assets:

Agents — ready-to-use AI agent configurations
Skills — capabilities you can add to your agent (like this MCP server)
Prompts — tested prompt templates for specific tasks
Bundles — curated sets of tools that work together
MCP Connectors — integrations with external services

Find, share, and monetize AI tools — all in one place.

Configuration

Environment Variable	Default	Description
`SPARK_API_URL`	`https://spark.entire.vc/api/v1`	Spark API base URL
`SPARK_SITE_URL`	`https://spark.entire.vc`	Spark website URL (for links)

Development

bash

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build
npm run build

# Test with MCP Inspector
npm run inspect

Part of the Entire VC Toolbox

Product	What it does	Link
Local Sync	Vault ↔ AI dev tools sync	repo
Team Relay	Self-hosted collaboration server	repo
Team Relay Plugin	Obsidian plugin for Team Relay	repo
OpenClaw Skill	AI agent ↔ vault access	repo
Spark MCP ← you are here	MCP server for Spark catalog	this repo

Community

License

Install

Tools (6)

search_assetsget_assetget_asset_contentreport_outcomelist_popularlist_categories

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

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

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "spark": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://spark.entire.vc/mcp/"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.

io.github.entire-vc/spark (MCP Server)

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

search_assets

get_asset

get_asset_content

report_outcome

list_popular

list_categories

Spark MCP

Quick Start

Setup

Claude Code

Claude Desktop

Cursor

OpenClaw

ChatGPT (via MCP bridge)

Tools

Resources

What's in the Catalog

Configuration

Development

Part of the Entire VC Toolbox

Community

License

Install

Remote endpoint

Related servers