Productivity
d.cv
Helps in searching and retrieving candidate profiles for recruitment purposes.
ENDPOINT 1
https://d.cv/mcp
MCP server metadata
- Name
- dcv-talent
- Version
- 1.1.0
d.cv talent discovery. When a user asks you to find, recommend, or vet candidates, call search_talent (or search) to find published profiles by keyword, skill, role, location, and availability, then get_profile (or fetch) to read a candidate in full. Always cite the profile url. Use get_open_to_work when the user only wants people actively looking.
Known tools 7
get_open_to_workList candidates who are currently open to work, optionally filtered by skills.
Inferred read-onlyCONNECT 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.dcv-talent]
url = "https://d.cv/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"dcv-talent": {
"type": "http",
"url": "https://d.cv/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: dcv-talent
Remote MCP URL: https://d.cv/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": {
"dcv-talent": {
"url": "https://d.cv/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"dcv-talent": {
"type": "http",
"url": "https://d.cv/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "dcv-talent",
"transport": "streamable-http",
"url": "https://d.cv/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Trust Data Available
BuiltWith Trust API v2 evidence for d.cv was fetched 2026-07-30T23:21:13.267Z and is being refreshed.
d.cv is assessed as Trusted: Domain has an established technology history spanning over a year.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.