TokenTally by Harlo is answering right now. Last checked 6 min ago. It exposes 4 tools.
Count tokens (o200k/cl100k), truncate to a budget, chunk text for RAG and estimate LLM cost.
Today is the operative word: we check TokenTally by Harlo every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 6 min ago.
claude mcp add tokentally --transport http https://tokentally.mike-tusa.workers.dev/mcp
https://tokentally.mike-tusa.workers.dev/mcp
[mcp_servers.tokentally]
url = "https://tokentally.mike-tusa.workers.dev/mcp"
{
"mcpServers": {
"tokentally": {
"url": "https://tokentally.mike-tusa.workers.dev/mcp"
}
}
}
{
"servers": {
"tokentally": {
"type": "http",
"url": "https://tokentally.mike-tusa.workers.dev/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
chunk_text
count_tokens
estimate_cost
truncate_to_budget
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://tokentally.mike-tusa.workers.dev/mcp | streamable-http | answering | 80 ms | 6 min ago |
Token counting, RAG chunking, truncation, HTML to Markdown and JSON repair
LLM-ready web search + instant answers + URL-to-clean-text fetch for agents and RAG.
Text extraction, keyword extraction, language detection, and chunking for RAG
Text extraction, keyword extraction, language detection, and chunking for RAG
Web pages and PDFs to clean, LLM-ready Markdown with token counts, small crawls and RAG chunks.
Convert PDF URLs to clean Markdown and text for RAG and LLM input. Pay per PDF on Apify.
Any URL to clean text, markdown, or JSON for LLM/RAG pipelines.
Turn any web page into clean Markdown, text or token-bounded RAG chunks (via RapidAPI).
Answers built from our own checks of this server.