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xianminx

Flomo MCP Server

by xianminx

newNote

Create and save notes in Flomo directly through AI chat interactions using natural language commands. Capture thoughts and information by typing your note content.

Instructions

Create a new note in Flomo

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes

Implementation Reference

  • index.ts:47-67 (handler)
    Inline asynchronous handler function for the 'newNote' tool. It calls createFlomoNote with the input value and returns the JSON-stringified response or error as MCP-formatted content.
    async (input) => {
      try {
        const response = await createFlomoNote(input.input);
        return {
          content: [
            {
              type: "text",
              text: `${JSON.stringify(response)}`,
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: `${JSON.stringify(error)}`,
            },
          ],
        };
      }
  • TypeScript interface defining the structure of the response from the Flomo API when creating a new note.
    interface FlomoNewNoteResponse {
      code: number;
      message: string;
      memo: {
        creator_id: number;
        source: string;
        content: string;
        tags: string[];
        updated_at: string;
        created_at: string;
        linked_memos: any[];
        linked_count: number;
        slug: string;
      };
    }
  • index.ts:43-69 (registration)
    Registration of the 'newNote' tool on the MCP server, including name, description, Zod input schema, and handler function.
    server.tool(
      "newNote",
      "Create a new note in Flomo",
      { input: z.string() },
      async (input) => {
        try {
          const response = await createFlomoNote(input.input);
          return {
            content: [
              {
                type: "text",
                text: `${JSON.stringify(response)}`,
              },
            ],
          };
        } catch (error) {
          return {
            content: [
              {
                type: "text",
                text: `${JSON.stringify(error)}`,
              },
            ],
          };
        }
      }
    );
  • Helper function that sends a POST request to the Flomo API to create a new note with the provided content.
    async function createFlomoNote(content: string): Promise<FlomoNewNoteResponse> {
      const body = {
        content: content,
      };
      return await fetch(flomoApiUrl, {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
        },
        body: JSON.stringify(body),
      }).then((res) => res.json());
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a note but doesn't describe what happens after creation (e.g., success/failure response, permissions needed, rate limits, or whether it's idempotent). This leaves significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential action and target system.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't address behavioral aspects, parameter meaning, or expected outcomes, leaving the agent with insufficient context to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no information about the single 'input' parameter. It doesn't explain what the input represents (e.g., note content, title, formatting), acceptable formats, or constraints, failing to compensate for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('a new note in Flomo'), providing a specific verb+resource combination. It doesn't need to distinguish from siblings since none exist, making the purpose sufficiently clear for standalone use.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It simply states what the tool does without any usage instructions or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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