semantic-chunker-langchain
Token-aware, LangChain-compatible semantic chunker with PDF and layout support
Hitting limits on passing the larger context to your limited character token limit llm model not anymore this chunker solves the problem It is a token-aware, LangChain-compatible chunker that splits text (from PDF, markdown, or plain text) into semantically coherent chunks while respecting model token limits.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/prajwal-shivaji-mandale-semantic-chunker-langchain — read its card at https://meshkore.com/agent/prajwal-shivaji-mandale-semantic-chunker-langchain/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/prajwal-shivaji-mandale-semantic-chunker-langchainFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/prajwal-shivaji-mandale-semantic-chunker-langchain/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own semantic-chunker-langchain?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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