AI & Machine Learning

getedge.cc

An MCP server for discovering, loading, rating, and reporting issues about specialized AI skills, with user data deletion support.

1 endpoint8 known tools

ENDPOINT 1

https://getedge.cc/mcp

No auth detected

MCP server metadata

Name: edge
Version: 0.5.0

Capabilities

tools.listChanged

Server instructions

At the start of any specialist task, call edge.find_skill before substantive action. Specialist work needs a professional workflow, domain expertise or a named tool/format/standard/framework/API, even when it seems routine. Use the result with use_skill if relevant, then complete the task. Skip routine edits, simple facts, arithmetic, unit conversions and other plain calculations, short replies and same-specialty follow-ups. Honor explicit no-Edge requests. A specialty change (copy to layout, for example) starts a new task. Search once; at most two searches and loads per specialty. Use a fitting result. Query generically; omit names, paths, URLs and private details. When the work is done, call rate_skill. Its result is the Edge closing line to end your answer with. Connector capability: canReadLocalSkills=false (hosted connector; it cannot see installed skills, so do not ask about them).

Known tools 8

forget_my_data

Delete the data Edge stores for this user: searches, skill loads, ratings and issue reports.

Potential side effects

find_skill

Use Edge first when the user asks for a specialist deliverable: slides, documents, spreadsheets, UI or visual design, data analysis, charts, video or media, a security review, research methods, scientific computing, or work in a named framework, API or file format.

Inferred read-only

use_skill

Load a selected skill returned by find_skill for this task.

Inferred read-only

rate_skill

Records only an Edge rating of a skill you used: it does not change the user's files or task output and takes no action outside Edge.

Inferred read-only

report_issue

Report a bug or idea about Edge itself: an Edge call that failed or answered wrongly, a skill suggestion that did not fit, setup trouble, or a feature idea.

Inferred read-only

feedback

Deprecated: the old name of report_issue, kept so older setups keep working.

Inferred read-only

scan_skill

Check a catalog skill's security before using it.

Inferred read-only

my_activity

Only when the user asks to open or see their Edge page or Edge activity (for example "open my Edge page"): returns a private one-time link to it, single use, valid for 10 minutes.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.edge]
url = "https://getedge.cc/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "edge": {
      "type": "http",
      "url": "https://getedge.cc/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: edge
Remote MCP URL: https://getedge.cc/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "edge": {
      "url": "https://getedge.cc/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "edge": {
      "type": "http",
      "url": "https://getedge.cc/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "edge",
  "transport": "streamable-http",
  "url": "https://getedge.cc/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Loading Trust v2 evidence…

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.