Skip to main content
Glama

create_tag

Add new tags to your Paperless-NGX instance by specifying a name, color, match string, and matching algorithm for automated document tagging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
colorNo
matchNo
matching_algorithmNo
nameYes

Implementation Reference

  • Handler function for the create_tag tool: validates API connection, calls api.createTag(args), enhances the tag with matching algorithm info, and returns JSON text content.
    withErrorHandling(async (args, extra) => { if (!api) throw new Error("Please configure API connection first"); const tag = await api.createTag(args); const enhancedTag = enhanceMatchingAlgorithm(tag); return { content: [ { type: "text", text: JSON.stringify(enhancedTag), }, ], }; })
  • Zod input schema for create_tag tool: requires name, optional color (hex), match, and matching_algorithm (0-6).
    { name: z.string(), color: z .string() .regex(/^#[0-9A-Fa-f]{6}$/) .optional(), match: z.string().optional(), matching_algorithm: z .number() .int() .min(0) .max(6) .optional() .describe(MATCHING_ALGORITHM_DESCRIPTION), },
  • MCP tool registration for create_tag using server.tool with schema and wrapped handler.
    server.tool( "create_tag", { name: z.string(), color: z .string() .regex(/^#[0-9A-Fa-f]{6}$/) .optional(), match: z.string().optional(), matching_algorithm: z .number() .int() .min(0) .max(6) .optional() .describe(MATCHING_ALGORITHM_DESCRIPTION), }, withErrorHandling(async (args, extra) => { if (!api) throw new Error("Please configure API connection first"); const tag = await api.createTag(args); const enhancedTag = enhanceMatchingAlgorithm(tag); return { content: [ { type: "text", text: JSON.stringify(enhancedTag), }, ], }; }) );
  • PaperlessAPI.createTag method: POST request to /tags/ with JSON data, called by the tool handler.
    async createTag(data: Partial<Tag>): Promise<Tag> { return this.request<Tag>("/tags/", { method: "POST", body: JSON.stringify(data), }); }

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/baruchiro/paperless-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server