Is Mcp Transcript safe to use?

Mcp Transcript has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.

How do I install Mcp Transcript?

Mcp Transcript can be installed by cloning its GitHub repository and following the setup instructions in the README.

What AI clients work with Mcp Transcript?

Mcp Transcript is compatible with Claude Desktop, Cursor, Claude Code, and most MCP clients that support stdio transport. It uses stdio transport.

Is Mcp Transcript actively maintained?

Mcp Transcript is actively maintained — last commit was 0 days ago.

Mcp Transcript

MCP server to parse Claude JSONL conversations and export structured Markdown learning logs

ActiveNot tested

AI / ML Writing

GitHub

30DNo CVEsactiveMIT

Quick Install

{
  "mcpServers": {
    "mcp-transcript": {
      "command": "<see-readme>",
      "args": []
    }
  }
}

Setup guide

No install config available. Check the server's README for setup instructions.

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/mcp-transcript)](https://mcppedia.org/s/mcp-transcript)

Should you use this server?

MCP server to parse Claude JSONL conversations and export structured Markdown learning logs

✓

Is it safe?

No package registry to scan.

No authentication — any process on your machine can connect.

MIT. View license →

✓

Is it maintained?

Last commit 0 days ago.

Will it work with my client?

Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.

README

🚀 MCP Transcript → PBL Generator

Server implementing MCP (Model Context Protocol) to process .jsonl transcripts
(Claude, ChatGPT exports, etc.) and generate Problem-Based Learning (PBL) logs in Markdown under docs/.

⚡ Turn raw AI conversations into structured, reusable knowledge.

🧠 What does it do?

This server:

📥 Parses .jsonl transcripts
🔍 Analyzes turns, errors, and structure
🧩 Extracts meaningful learning insights (PBL-style)
📝 Generates clean Markdown logs inside docs/

⚡ Quick Start

npm install
npm run start

Server endpoint:

http://localhost:3000/mcp

🔌 MCP Flow (Mental Model)

Initialize session
(Optional) Confirm initialization
Call tools

👉 Think of it like a stateful API session

🛠️ Available Tools

transcript_health → Quick diagnostics of transcript integrity
pbl_parse_jsonl → Parses and structures transcript data
pbl_export_markdown → Generates a PBL learning log in Markdown

🔧 Example: Full Flow

1) Initialize Session

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "initialize",
    "params": {
      "protocolVersion": "2025-03-26",
      "capabilities": {},
      "clientInfo": {
        "name": "curl-client",
        "version": "1.0.0"
      }
    }
  }'

👉 Save the mcp-session-id from response headers.

2) Send Initialized Notification (Recommended)

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "method": "notifications/initialized",
    "params": {}
  }'

🧪 Tool Usage Examples

🔍 Parse Transcript

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "id": 2,
    "method": "tools/call",
    "params": {
      "name": "pbl_parse_jsonl",
      "arguments": {
        "inputPath": "/path/to/transcript.jsonl"
      }
    }
  }'

Returns:

Summary (lines, turns, errors)
Structured data (turns, preview, etc.)

📝 Export PBL Markdown

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "id": 3,
    "method": "tools/call",
    "params": {
      "name": "pbl_export_markdown",
      "arguments": {
        "inputPath": "/path/to/transcript.jsonl",
        "outputPath": "docs/pbl/my-learning-log.md",
        "title": "Learning Log - Sprint 1",
        "projectName": "My MCP Server"
      }
    }
  }'

📁 Output Behavior

If outputPath is NOT provided:

docs/pbl/<input-file-name>-pbl.md

Security restriction:
- Only paths inside docs/ are allowed
docs/ is ignored by Git (.gitignore)

⚡ CLI Usage (NPX)

npx mcp-transcript

Runs MCP over stdio (perfect for local integrations / Codex workflows)

🔧 Environment Variables

PORT → default 3000
MCP_PATH → default /mcp
ALLOWED_ORIGINS → CSV
SESSION_TTL_MS
RATE_LIMIT
RATE_WINDOW_MS

💡 Why this exists

Working with AI generates a LOT of knowledge… but it’s messy.

This tool helps you:

Convert conversations → learning artifacts
Build personal knowledge bases
Track problem-solving evolution
Reuse insights instead of losing them

Test This Server

No automated test available for this server. Check the GitHub README for setup instructions.

Help improve this page

This server is missing a description. Tools and install config are also missing.If you've used it, help the community.

Add information

Score Breakdown

MCPpedia Score

Click each category to see evidence

30D

Last scored 9h ago

How we score →

Security

5/30

No known vulnerabilities.

○

Known CVEs — No package registry to scan

○

Tool safety — No tools to analyze

○

Tool poisoning — No tools to analyze

○

Injection vectors — No tools to analyze

○

Tool stability — First scan — baseline recorded

○

Dependency health — No package to analyze

✓

License — License: MIT

○

Authentication — No authentication required

○

Repository — active repo

CVEs checked daily via OSV.dev. Score algorithm is open source.

Reviews

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is Mcp Transcript safe to use?: Mcp Transcript has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.
How do I install Mcp Transcript?: Mcp Transcript can be installed by cloning its GitHub repository and following the setup instructions in the README.
What AI clients work with Mcp Transcript?: Mcp Transcript is compatible with Claude Desktop, Cursor, Claude Code, and most MCP clients that support stdio transport. It uses stdio transport.
Is Mcp Transcript actively maintained?: Mcp Transcript is actively maintained — last commit was 0 days ago.

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Discussion

Start a conversation

Ask a question, share a tip, or report an issue.

Has anyone used this with Cursor?How do you handle auth?Any alternatives?

🚀 MCP Transcript → PBL Generator

Server implementing MCP (Model Context Protocol) to process .jsonl transcripts
(Claude, ChatGPT exports, etc.) and generate Problem-Based Learning (PBL) logs in Markdown under docs/.

⚡ Turn raw AI conversations into structured, reusable knowledge.

🧠 What does it do?

This server:

📥 Parses .jsonl transcripts
🔍 Analyzes turns, errors, and structure
🧩 Extracts meaningful learning insights (PBL-style)
📝 Generates clean Markdown logs inside docs/

⚡ Quick Start

npm install
npm run start

Server endpoint:

http://localhost:3000/mcp

🔌 MCP Flow (Mental Model)

Initialize session
(Optional) Confirm initialization
Call tools

👉 Think of it like a stateful API session

🛠️ Available Tools

transcript_health → Quick diagnostics of transcript integrity
pbl_parse_jsonl → Parses and structures transcript data
pbl_export_markdown → Generates a PBL learning log in Markdown

🔧 Example: Full Flow

1) Initialize Session

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "initialize",
    "params": {
      "protocolVersion": "2025-03-26",
      "capabilities": {},
      "clientInfo": {
        "name": "curl-client",
        "version": "1.0.0"
      }
    }
  }'

👉 Save the mcp-session-id from response headers.

2) Send Initialized Notification (Recommended)

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "method": "notifications/initialized",
    "params": {}
  }'

🧪 Tool Usage Examples

🔍 Parse Transcript

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "id": 2,
    "method": "tools/call",
    "params": {
      "name": "pbl_parse_jsonl",
      "arguments": {
        "inputPath": "/path/to/transcript.jsonl"
      }
    }
  }'

Returns:

Summary (lines, turns, errors)
Structured data (turns, preview, etc.)

📝 Export PBL Markdown

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'mcp-session-id: YOUR_SESSION_ID' \
  -d '{
    "jsonrpc": "2.0",
    "id": 3,
    "method": "tools/call",
    "params": {
      "name": "pbl_export_markdown",
      "arguments": {
        "inputPath": "/path/to/transcript.jsonl",
        "outputPath": "docs/pbl/my-learning-log.md",
        "title": "Learning Log - Sprint 1",
        "projectName": "My MCP Server"
      }
    }
  }'

📁 Output Behavior

If outputPath is NOT provided:

docs/pbl/<input-file-name>-pbl.md

Security restriction:
- Only paths inside docs/ are allowed
docs/ is ignored by Git (.gitignore)

⚡ CLI Usage (NPX)

npx mcp-transcript

Runs MCP over stdio (perfect for local integrations / Codex workflows)

🔧 Environment Variables

PORT → default 3000
MCP_PATH → default /mcp
ALLOWED_ORIGINS → CSV
SESSION_TTL_MS
RATE_LIMIT
RATE_WINDOW_MS

💡 Why this exists

Working with AI generates a LOT of knowledge… but it’s messy.

This tool helps you:

Convert conversations → learning artifacts
Build personal knowledge bases
Track problem-solving evolution
Reuse insights instead of losing them