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Evc Spark MCP

by entire-vc

Searches Spark’s catalog of AI agents, skills, prompts, bundles, and MCP connectors, then retrieves content and records usage outcomes.

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Install Evc Spark MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "entire-vc-evc-spark-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "evc-spark-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— the server itself is confirmed live (we called its tools/list endpoint). The stdio install command is a separate, ongoing check.

Overview

The entire-vc/evc-spark-mcp MCP server connects AI clients to Spark, a catalog of agents, skills, prompts, bundles, and MCP connectors. It supports catalog search, asset inspection, content retrieval, popularity and category browsing, API quota checks, and outcome reporting. Run it through npx in an MCP-compatible client; no API key is needed for trial access, while SPARK_API_KEY enables full search access. Reach for it when an agent needs to discover reusable AI workflow assets or provide feedback on assets it applied.

Use cases

  • Search for agents, skills, prompts, bundles, or MCP connectors
  • Inspect a Spark asset before applying it
  • Retrieve raw prompt or skill content by asset slug
  • Browse popular assets and filter by category
  • Report whether fetched content worked or failed

Key features

  • Searches Spark assets by query, type, and domain
  • Retrieves asset details and raw content
  • Lists popular assets and available categories
  • Checks API key status and daily usage
  • Records application outcomes with an application ID
  • Provides asset and catalog MCP resources

Tools7

What Evc Spark MCP lets your agent do. Expand a tool for its parameters.

Verified live~1.2k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

19/19 checks healthy over the last 79d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 10d ago via OSV.dev · evc-spark-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars4Stargazers on the source repository.
npm downloads147Package downloads in the last 30 days.
Last commit2d agoMost recent push to the default branch.
Tools exposed7Callable tools this server registers over MCP.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How Evc Spark MCP works

What entire-vc/evc-spark-mcp MCP server does

The entire-vc/evc-spark-mcp MCP server exposes Spark’s AI asset marketplace through MCP. Spark contains several asset types: agent configurations, skills, prompt templates, bundles, and connectors for external services. Agents can search the catalog, inspect an individual asset, retrieve its underlying content, and use catalog metadata to narrow discovery.

The server is suited to workflows where an AI client needs to find a reusable instruction set or agent configuration rather than create one from scratch. It can also support asset evaluation: after content is retrieved and applied, the client can submit an outcome describing whether it worked unchanged, required edits, failed, or was not relevant.

How it works

Launch the package with npx evc-spark-mcp and connect the resulting stdio process to an MCP client. The server communicates with Spark’s API and makes catalog operations available as MCP tools. Asset records can be addressed by slug, and the server also provides resource URI patterns for asset content and catalog listings.

search_assets accepts a query with type and domain filtering. get_asset returns expanded information such as descriptions, files, and outcome reports. get_asset_content retrieves raw prompt, skill, or agent material and produces an application ID for later feedback. list_popular and list_categories help with discovery when the client does not have a specific search term.

Trial requests work without credentials and return up to five search results. Supplying SPARK_API_KEY provides full access according to the account’s quota. get_api_key_info reports key status, daily serving totals, and remaining allowance. Outcome fields are visible to the asset author, so submissions should exclude private paths, credentials, personal contact details, client data, and token-bearing URLs.

Setup and configuration

The package can be added to Claude Code with claude mcp add spark -- npx -y evc-spark-mcp. Claude Desktop and Cursor use an MCP server entry whose command is npx and whose argument is -y evc-spark-mcp.

No environment variable is required for the basic launch. SPARK_API_KEY is optional and enables full catalog access. SPARK_API_URL can override the default Spark API endpoint, while SPARK_SITE_URL changes the website base used for links. The repository includes npm commands for dependency installation, development mode, building, and MCP Inspector testing.

The entire-vc/evc-spark-mcp MCP server is released under the MIT license.

Read the full README View source on GitHub

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Frequently Asked Questions about Evc Spark MCP

entire-vc/evc-spark-mcp is an MCP server that connects AI clients to Spark’s catalog of agents, skills, prompts, bundles, and MCP connectors. Its main tools search assets, retrieve details or raw content, list popular items and categories, check API usage, and report outcomes after applying fetched content.

Run `npx evc-spark-mcp`, or add that command to your MCP client configuration. The README provides specific entries for Claude Code, Claude Desktop, Cursor, and OpenClaw, and says other MCP-compatible clients can use the same command.

No, an API key is not required for basic use. Anonymous trial searches are limited to five results; setting `SPARK_API_KEY` enables full access subject to the account’s quota.

Use `report_outcome` after applying content obtained with `get_asset_content`. Submit the application ID and classify the result as applied as is, applied with changes, broke, or not applicable; repeated reports for the same ID update the existing report.

Claude Code, Claude Desktop, Cursor, and OpenClaw are documented configurations.

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