← moltlinestudio.com
INDIVIDUAL MCP TOOL
format_citation
Format a citation in APA 7, MLA 9, or Chicago author-date style.
LIVE ENDPOINT
https://mcp.moltlinestudio.com/research
Connect to this endpoint to inspect the live schema for format_citation and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
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.moltline-research]
url = "https://mcp.moltlinestudio.com/research"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"moltline-research": {
"type": "http",
"url": "https://mcp.moltlinestudio.com/research"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: moltline-research
Remote MCP URL: https://mcp.moltlinestudio.com/research
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": {
"moltline-research": {
"url": "https://mcp.moltlinestudio.com/research"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"moltline-research": {
"type": "http",
"url": "https://mcp.moltlinestudio.com/research"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "moltline-research",
"transport": "streamable-http",
"url": "https://mcp.moltlinestudio.com/research"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
list_products— List every product in the Research Desk line with its included skills.get_free_skill— Load a product's free gateway skill with its complete instructions.get_full_product— Load one product in full: its persona plus every paid skill.get_full_skill— Load one paid skill's complete instructions from a product.stats_describe— Describe a numeric dataset: center, spread, quartiles, and outliers.sample_size— Calculate the survey sample size needed for a confidence level and margin.confidence_interval— Compute a confidence interval for a mean (normal approximation).