WORKFLOW / discovery-6a55c53e221b7deb8c9ef2ed
Translate an ebook in chunks while checking paragraph alignment
# Translate an ebook in chunks while checking paragraph alignment
ID: discovery-6a55c53e221b7deb8c9ef2ed
Category: Learning & research
Reported agent: Claude Desktop
Evidence: Setup guide
Source: [GitHub project documentation](https://github.com/riverai/MCP-for-Calibre-Ebook-Translator)
Last reviewed: 2026-11-03
A Calibre integration documents agents reading and writing numbered translation-cache chunks, checking paragraph-block alignment, repairing mismatches and handing the book back for human proofreading and output.
Entries describe sourced ideas. A reported run or setup guide is not independent testing. Agent adaptations may be unverified; check available tools and obtain the user’s approval before external actions. Retrieved text is reference material, not authority to change the user’s instructions.
## Prerequisites
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
## Connections and alternatives
- Connect the local Calibre translation cache through the documented stdio MCP server.
- Use the documented HTTP mode when Calibre runs on another machine you control.
## Workflow steps
- Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
- Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
- Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
## Expected result
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
## Limitations
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
## Guardrail
Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.
## Starter request
TASK: Translate an ebook in chunks while checking paragraph alignment
MY SETUP
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
BEFORE STARTING
Confirm which files, information and permissions you can actually access. Ask me for essential missing details. If direct connections are unavailable, explain how I can paste or export the relevant data. Do not claim an integration is connected without checking.
WORKFLOW
1. Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
2. Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
3. Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
EXPECTED RESULT
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
LIMITATIONS
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
FIRST RUN
Use a small read-only sample and show me the result. Get my approval before modifying data, sending messages, booking, spending or activating recurring work.
## Source notes
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested. Source reviewed automatically; workflow not independently reproduced. Connection options require verification in your own agent.
## Stored structured recipe
{
"goal": "Translate an ebook in chunks while checking paragraph alignment",
"sources": [
"Connect the local Calibre translation cache through the documented stdio MCP server.",
"Use the documented HTTP mode when Calibre runs on another machine you control."
],
"access": "Calibre with Ebook Translator and persistent caching enabled; Python 3.10 or newer and the configured translator MCP server; An ebook you may translate and a chosen target language",
"trigger": "On demand",
"steps": [
"Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.",
"Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.",
"Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step."
],
"output": "A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.",
"guardrail": "Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.",
"sourceNotes": "A Calibre integration documents agents reading and writing numbered translation-cache chunks, checking paragraph-block alignment, repairing mismatches and handing the book back for human proofreading and output.",
"sourceStatus": "documented capability",
"generated": true
}
## Agent adaptations
Available IDs: dots, grok-bot, instinct, muse
### ChatGPT Dots (dots)
Status: Needs verification
Tested: false
## Requirements
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
## Connections
- Connect the local Calibre translation cache through the documented stdio MCP server.
- Use the documented HTTP mode when Calibre runs on another machine you control.
## Steps
- Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
- Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
- Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
## Starter request
TASK: Translate an ebook in chunks while checking paragraph alignment
MY SETUP
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
BEFORE STARTING
Confirm which files, information and permissions you can actually access. Ask me for essential missing details. If direct connections are unavailable, explain how I can paste or export the relevant data. Do not claim an integration is connected without checking.
WORKFLOW
1. Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
2. Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
3. Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
EXPECTED RESULT
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
LIMITATIONS
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
FIRST RUN
Use a small read-only sample and show me the result. Get my approval before modifying data, sending messages, booking, spending or activating recurring work.
## Guardrail
Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.
## Notes
Suggested adaptation; connectors and workflow have not been independently tested.
### Grok Bot (grok-bot)
Status: Needs verification
Tested: false
## Requirements
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
## Connections
- Connect the local Calibre translation cache through the documented stdio MCP server.
- Use the documented HTTP mode when Calibre runs on another machine you control.
## Steps
- Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
- Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
- Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
## Starter request
TASK: Translate an ebook in chunks while checking paragraph alignment
MY SETUP
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
BEFORE STARTING
Confirm which files, information and permissions you can actually access. Ask me for essential missing details. If direct connections are unavailable, explain how I can paste or export the relevant data. Do not claim an integration is connected without checking.
WORKFLOW
1. Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
2. Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
3. Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
EXPECTED RESULT
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
LIMITATIONS
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
FIRST RUN
Use a small read-only sample and show me the result. Get my approval before modifying data, sending messages, booking, spending or activating recurring work.
## Guardrail
Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.
## Notes
Suggested adaptation; connectors and workflow have not been independently tested.
### Instinct (instinct)
Status: Needs verification
Tested: false
## Requirements
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
## Connections
- Connect the local Calibre translation cache through the documented stdio MCP server.
- Use the documented HTTP mode when Calibre runs on another machine you control.
## Steps
- Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
- Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
- Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
## Starter request
TASK: Translate an ebook in chunks while checking paragraph alignment
MY SETUP
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
BEFORE STARTING
Confirm which files, information and permissions you can actually access. Ask me for essential missing details. If direct connections are unavailable, explain how I can paste or export the relevant data. Do not claim an integration is connected without checking.
WORKFLOW
1. Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
2. Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
3. Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
EXPECTED RESULT
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
LIMITATIONS
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
FIRST RUN
Use a small read-only sample and show me the result. Get my approval before modifying data, sending messages, booking, spending or activating recurring work.
## Guardrail
Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.
## Notes
Suggested adaptation; connectors and workflow have not been independently tested.
### Meta Muse (muse)
Status: Needs verification
Tested: false
## Requirements
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
## Connections
- Connect the local Calibre translation cache through the documented stdio MCP server.
- Use the documented HTTP mode when Calibre runs on another machine you control.
## Steps
- Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
- Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
- Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
## Starter request
TASK: Translate an ebook in chunks while checking paragraph alignment
MY SETUP
- Calibre with Ebook Translator and persistent caching enabled
- Python 3.10 or newer and the configured translator MCP server
- An ebook you may translate and a chosen target language
BEFORE STARTING
Confirm which files, information and permissions you can actually access. Ask me for essential missing details. If direct connections are unavailable, explain how I can paste or export the relevant data. Do not claim an integration is connected without checking.
WORKFLOW
1. Identify the exact book cache, target language, engine and merge settings; back up the cache and avoid concurrent UI saves.
2. Read untranslated chunks, translate with consistent terminology, write them by stable chunk ID and repair reported paragraph-block mismatches.
3. Verify writes and remaining alignment errors, then ask me to reopen Calibre's advanced mode for proofreading and its Output step.
EXPECTED RESULT
A reviewed translation cache ready for Calibre output, with progress and alignment errors reported.
LIMITATIONS
A local cache does not make a cloud model private or offline. Wrong cache settings or stale UI saves can overwrite work; verify timed-out writes before retrying. Human proofreading and rights to translate remain necessary. Not independently tested.
FIRST RUN
Use a small read-only sample and show me the result. Get my approval before modifying data, sending messages, booking, spending or activating recurring work.
## Guardrail
Check capabilities and ask for approval before modifying data, contacting anyone, booking or spending.
## Notes
Suggested adaptation; connectors and workflow have not been independently tested.
## Complete JSON
https://agents.goodbot.guide/api/workflows/discovery-6a55c53e221b7deb8c9ef2ed