Enables curation of enterprise knowledge from Slack threads, extracting validated Q&A resolution pairs, removing duplicate organizational knowledge, and synthesizing structured Markdown SOP runbooks.
Enables curation of enterprise knowledge from WeChat Work threads, extracting validated Q&A resolution pairs, removing duplicate organizational knowledge, and synthesizing structured Markdown SOP runbooks.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@genpark-enterprise-slack-wecom-knowledge-base-auto-curator-skill extract the resolved Q&A from this Slack thread and make an SOP runbook"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
Enterprise Slack & WeChat Work Thread Knowledge Base Auto-Curator. Parses messy multi-turn troubleshooting conversations, extracts validated Q&A resolution pairs, removes duplicate organizational knowledge, and synthesizes structured Markdown SOP runbooks.
GenPark Official Website: https://www.genpark.ai
LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
Related MCP server: mcp-rag-agent
100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library.
Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0 initialize, tools/list, and tools/call.
Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.
from client import EnterpriseChatKnowledgeBaseAutoCurator
def main():
curator = EnterpriseChatKnowledgeBaseAutoCurator()
chat = [
{"author": "Charlie", "text": "Redis cluster OOM kill on shard 2 after morning cron."},
{"author": "David", "text": "Root cause was bigkey in analytics:user:sessions without TTL. Flushed key and added 24h expiration policy."},
{"author": "Charlie", "text": "Verified working now, thanks!"}
]
sop = curator.curate_knowledge_sop(chat, "Redis Shard OOM BigKey Remediation")
print("--- Enterprise Auto-Curated SOP ---")
print(sop['sop_markdown'])
if __name__ == "__main__":
main()
Start standard JSON-RPC 2.0 server over stdio:
python mcp_server.pyExecute embedded test harness:
python mcp_server.py --testInspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
Licensed under the MIT License. Copyright Β© 2026 GenPark AI. Follow us on LinkedIn: https://www.linkedin.com/company/92955550 | https://www.llinkedin.com/company/92955550
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