Skip to main content
Glama

image-to-markdown

Convert images to markdown format with metadata and descriptions for easy integration into documentation and content.

Instructions

Convert an image to markdown, including metadata and description

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYesAbsolute path of the image file to convert

Implementation Reference

  • Core handler function that performs the image-to-markdown conversion by executing the markitdown tool via uv on the provided filepath, handling temporary files, and returning the markdown output path and text.
    static async toMarkdown({
      filePath,
      url,
      projectRoot = path.resolve(__dirname, ".."),
      uvPath = "~/.local/bin/uv",
    }: {
      filePath?: string;
      url?: string;
      projectRoot?: string;
      uvPath?: string;
    }): Promise<MarkdownResult> {
      try {
        let inputPath: string;
        let isTemporary = false;
    
        if (url) {
          const response = await fetch(url);
    
          let extension = null;
    
          if (url.endsWith(".pdf")) {
            extension = "pdf";
          }
    
          const arrayBuffer = await response.arrayBuffer();
          const content = Buffer.from(arrayBuffer);
    
          inputPath = await this.saveToTempFile(content, extension);
          isTemporary = true;
        } else if (filePath) {
          inputPath = filePath;
        } else {
          throw new Error("Either filePath or url must be provided");
        }
    
        const text = await this._markitdown(inputPath, projectRoot, uvPath);
        const outputPath = await this.saveToTempFile(text);
    
        if (isTemporary) {
          fs.unlinkSync(inputPath);
        }
    
        return { path: outputPath, text };
      } catch (e: unknown) {
        if (e instanceof Error) {
          throw new Error(`Error processing to Markdown: ${e.message}`);
        } else {
          throw new Error("Error processing to Markdown: Unknown error occurred");
        }
      }
    }
  • Input schema definition for the image-to-markdown tool, specifying the required filepath parameter.
    export const ImageToMarkdownTool = ToolSchema.parse({
      name: "image-to-markdown",
      description:
        "Convert an image to markdown, including metadata and description",
      inputSchema: {
        type: "object",
        properties: {
          filepath: {
            type: "string",
            description: "Absolute path of the image file to convert",
          },
        },
        required: ["filepath"],
      },
    });
  • src/server.ts:33-37 (registration)
    Registers the image-to-markdown tool (along with others) by including it in the list of available tools returned via Object.values(tools).
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: Object.values(tools),
      };
    });
  • Dispatch handler in the tool call switch statement that matches image-to-markdown and invokes the Markdownify.toMarkdown helper with the filepath argument.
    case tools.PDFToMarkdownTool.name:
    case tools.ImageToMarkdownTool.name:
    case tools.AudioToMarkdownTool.name:
    case tools.DocxToMarkdownTool.name:
    case tools.XlsxToMarkdownTool.name:
    case tools.PptxToMarkdownTool.name:
      if (!validatedArgs.filepath) {
        throw new Error("File path is required for this tool");
      }
      result = await Markdownify.toMarkdown({
        filePath: validatedArgs.filepath,
        projectRoot: validatedArgs.projectRoot,
        uvPath: validatedArgs.uvPath || process.env.UV_PATH,
      });
      break;
  • Private helper method that executes the markitdown binary using uv run to convert the image file to markdown text.
    private static async _markitdown(
      filePath: string,
      projectRoot: string,
      uvPath: string,
    ): Promise<string> {
      const venvPath = path.join(projectRoot, ".venv");
      const markitdownPath = path.join(
        venvPath,
        process.platform === "win32" ? "Scripts" : "bin",
        `markitdown${process.platform === "win32" ? ".exe" : ""}`,
      );
    
      if (!fs.existsSync(markitdownPath)) {
        throw new Error("markitdown executable not found");
      }
    
      // Expand tilde in uvPath if present
      const expandedUvPath = expandHome(uvPath);
    
      // Use execFile to prevent command injection
      const { stdout, stderr } = await execFileAsync(expandedUvPath, [
        "run",
        markitdownPath,
        filePath,
      ]);
    
      if (stderr) {
        throw new Error(`Error executing command: ${stderr}`);
      }
    
      return stdout;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the conversion includes metadata and description, which adds some context about output behavior. However, it lacks details on error handling, performance characteristics, or any side effects, leaving gaps in understanding how the tool behaves beyond the basic operation.

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 that directly states the tool's function without unnecessary words. It is front-loaded with the core purpose and includes a brief mention of output features, making it easy to understand quickly. Every part of the sentence contributes to clarifying the tool's role.

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

Completeness3/5

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

Given the tool's moderate complexity (conversion with metadata) and lack of annotations and output schema, the description is minimally adequate. It covers the basic operation and hints at output content but does not fully address behavioral aspects or provide complete context for effective use. The description meets the minimum viable standard but has clear gaps in usage and transparency.

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

Parameters3/5

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

The input schema has 100% description coverage, clearly documenting the single parameter 'filepath' as the absolute path of the image file. The description does not add any additional meaning beyond what the schema provides, such as supported image formats or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

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 tool's purpose: converting an image to markdown, including metadata and description. It specifies the verb 'convert' and the resource 'image', distinguishing it from sibling tools that handle other file types like audio, PDF, or webpage. However, it does not explicitly differentiate from siblings beyond the resource type, as all sibling tools involve conversion to markdown.

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. It does not mention prerequisites, such as the image file needing to be accessible or in a specific format, or when to choose this over other markdown conversion tools for different content types. Usage is implied by the tool name but not explicitly stated.

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

Install Server

Other Tools

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/zcaceres/markdownify-mcp'

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