OneTool solves the MCP token tax problem by exposing 100+ tools through a single server instead of dozens. Instead of loading tool definitions that burn 3K-30K tokens per server, your agent writes Python code like `__run brave.search(query="react docs")` to call tools on demand. You get Brave search, Google Grounding, Tavily, Context7 docs, database queries, Excalidraw diagrams, file operations, Excel handling, Playwright browser automation, and Chrome DevTools utilities all from one connection. It includes smart context stores backed by SQLite FTS5, image vision routing to cheaper models, and LLM-powered text compaction. The architecture cuts token overhead by 96% compared to running separate MCP servers for each capability, which matters when you're paying per million tokens.
🧿 One MCP for developers - no tool tax, no context rot.
250+ tools your agent calls as Python code: search, docs, files, databases, diagrams, vision, memory - plus a proxy for every MCP server you already use.
Works with Claude Code, Cursor, Codex - any MCP client
Every MCP server re-sends its tool definitions on every request: 3K-30K tokens each. Connect 5 servers and you've burned 55K tokens before the conversation starts. Connect 10+ and you're at 100K.
The math is brutal: Claude Opus 4.5 at $5/M input tokens, 20 days × 10 conversations × 10 messages × 3K tokens = $30/month per MCP server - even if you never use the tools.
And then there's context rot - your AI literally gets dumber as you add more tools (Chroma Research, 2025).
OneTool is one MCP server that exposes tools as a Python API. Instead of reading tool definitions, your agent writes code:
__onetool brave.search(query="react 19 server components")
Configure one MCP server. Use unlimited tools - ~2K tokens no matter how many you add.
"Agents scale better by writing code to call tools instead. This reduces the token usage from 150,000 tokens to 2,000 tokens...a cost saving of 98.7%"
97% fewer tokens. 30× lower cost. No context rot. (Measured - 47,660 → 1,131 input tokens against 18 MCP servers.)
Because tools are Python functions, your agent does things tool-call JSON can't: batch, chain, loop, compose.
__onetool
page = webfetch.fetch(url="https://fastmcp.dev/changelog", output_format="markdown")
notes = ot_llm.transform(data=page, prompt="Summarise the breaking changes")
mem.write(topic="deps/fastmcp", content=notes)
Three packs, one request. Intermediate results flow between tools as variables - the page body never touches your context window, and the summarising runs on a cheap model instead of your expensive coding agent.
Every call is explicit and reviewable - __onetool brave.search(query="...") shows you exactly what runs. No tool-selection guessing.
And the runtime is built for how agents actually type:
mem.search(q="auth") works - any unambiguous parameter prefix resolves (q= → query=)wb.draw(...) works - packs have short aliases (wb, ctx, img)github.listRepositories() works on proxied servers - snake/camel/Pascal all resolveBootstrap (installs uv if missing, installs OneTool, initialises config, prints MCP config):
curl -LsSf https://onetool.beycom.online/install.sh | sh # macOS / Linux
irm https://onetool.beycom.online/install.ps1 | iex # Windows (PowerShell)
Or install manually with uv:
uv tool install 'onetool-mcp[all]' # everything
onetool init --config ~/.onetool
Then print ready-to-paste MCP client config with resolved absolute paths and add it
to your client (claude-code, claude-desktop, cursor, or vscode):
onetool init mcp-config --client claude-code # or omit --client for all four
That's it. All 250+ tools work out of the box.
Verify: onetool init validate --config ~/.onetool/onetool.yaml
Install the ot-ref skill into your agent with vercel-labs/skills - it teaches the call conventions and ships a greppable index of every tool signature:
npx skills add https://github.com/beycom/onetool-mcp --skill ot-ref --agent claude
| Search & docs | Brave, Google-grounded, and Tavily search (each with batch + answer modes), Context7 library docs, web fetch with extraction controls |
| Files & data | File ops with path boundaries, full Excel control, SQL databases, PDF/Word/PowerPoint → Markdown, ripgrep, package versions |
| Context economy | ctx handles for large outputs, partial file reads (toc/slice), image vision on a dedicated cheap model (zero host tokens), LLM delegation (10× savings) |
| Persistent state | mem memory with semantic + keyword search, history and rollback; knowledge RAG bases with AI enrichment; localhist Git-backed project snapshots |
| Visual | Live Excalidraw whiteboard with a Mermaid-compatible DSL and offline auto-layout, Mermaid/PlantUML/D2 diagrams, architecture models → draw.io-editable SVG |
| Runtime | MCP server proxy with runtime enable/disable/restart, direct CLI/API into the running process, ot-ref agent skill, in-conversation tool forging |
| Trust | age-encrypted secrets backed by your OS keychain, AST validation, path boundaries, output sanitisation, runtime stats with estimated savings |
28 packs, 253 tools ready to use (console in beta):
| Pack | Tools | Extra | Description |
|---|---|---|---|
arch | generate, validate, bundle_solution, … | [dev] | Architecture models → draw.io-editable SVG |
brave | search, news, image, video, search_batch | [util] | Brave web search |
chrome_util | highlight_element, guide_user, … | [dev] | Browser annotations (Chrome DevTools) |
console (beta) | show, display, list, read, clear | Messages to the upcoming onetool-console app | |
context7 | search, doc | [dev] | Library documentation |
convert | pdf, word, powerpoint, excel, auto | [util] | Documents → Markdown |
db | query, schema, tables, sample | [dev] | SQL databases |
diagram | render_diagram, batch_render, get_template, … | [dev] | Mermaid / PlantUML / D2 via Kroki |
excel | read, write, formula, create_table, … (24 tools) | [util] | Full Excel control |
file | read, write, edit, grep, slice, toc, … (16 tools) | [util] | File ops with path boundaries |
ground | search, dev, docs, reddit, search_batch | [util] | Google-grounded search with sources |
knowledge | search, ask, write, related, … (15 tools) | [util] | RAG knowledge bases (hybrid search) |
localhist | save, diff, restore, autosave_start, … (15 tools) | [dev] | Git-backed local history snapshots |
mem | write, search, ask, history, rollback, … (31 tools) | [util] | Persistent memory with semantic search |
ot | help, tools, stats, status, result, … (18 tools) | Introspection and management | |
ot_context (ctx) | write, read, grep, slice, toc, ask, … (13 tools) | Smart context store for large outputs | |
ot_forge | create_ext, validate_ext | Scaffold new tool packs | |
ot_image (img) | load, ask, clip_ask, summary, … (9 tools) | Image vision via a dedicated model | |
ot_llm | transform, transform_file | LLM-powered transforms | |
ot_secrets | set, encrypt, audit, rotate, … (8 tools) | Encrypted secrets management | |
ot_servers | enable, disable, restart, status | Runtime control of proxied servers | |
ot_timer | start, stop, elapsed, list, clear | Named timers | |
package | pypi, npm, version, audit, models | [dev] | Package versions and staleness |
play_util | highlight_element, guide_user, … | [dev] | Browser annotations (Playwright) |
ripgrep | search, count, files, types | [dev] | Fast code search |
tavily | search, research, extract, search_batch, … | [util] | AI-native search and extraction |
webfetch | fetch, fetch_batch | [dev] | Web content extraction |
whiteboard (wb) | open, draw, layout, screenshot, … (22 tools) | [util] | Live Excalidraw canvas |
📖 Complete tools reference — every signature, generated from source
Keep the MCP servers you already use. Wrap them in YAML and call them explicitly - as Python namespaces, without their tool tax:
# .onetool/onetool.yaml
servers:
local_tools:
type: stdio
command: npx
args: ["-y", "some-mcp-server@latest"]
private_api:
type: http
url: ${PRIVATE_MCP_URL}
auth:
type: bearer
token: ${PRIVATE_MCP_TOKEN}
__onetool private_api.read_resource(path="README.md")
Proxied servers can be enabled, disabled, and restarted mid-conversation with ot_servers - no client restart.
onetool init walks you through encrypted secrets: values in secrets.yaml are age-encrypted, the private key lives in your OS keychain, and decryption happens transparently at load.
# secrets.yaml - safe to inspect, safe to commit
brave_api_key: age1enc:YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNT...
Works as an MCP server and as a direct CLI bridge into the same running process - loaded config, secrets, and proxy connections stay warm. Useful for agent harnesses, scripts, and automation:
# Recommended local MCP root mode: stdio
onetool serve --config .onetool/onetool.yaml
# URL-based MCP root mode for containerized clients
onetool serve --transport http --config .onetool/onetool.yaml --host 127.0.0.1 --port 8767 --path /mcp
# Enable the MCP-owned direct API in onetool.yaml:
# direct.host.enabled: true
# Start OneTool as MCP, then use the port printed in startup logs.
onetool direct run --port 8765 "ot.packs()" --format json | jq '.[0].name'
onetool direct run --port 8765 "brave.search(query='latest AI news')" --format raw
Drop a Python file, get a pack. No registration, no config:
# .onetool/tools/wiki.py
pack = "wiki"
def summary(*, title: str) -> str:
"""Get Wikipedia article summary."""
import httpx
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{title}"
return httpx.get(url).json().get("extract", "Not found")
__onetool wiki.summary(title="Python_(programming_language)")
OneTool sends anonymous startup pings (event type, version, OS). No personal data. Opt out: export DO_NOT_TRACK=1 or set telemetry.enabled: false in onetool.yaml. Details
Check for existing issues first:
is:issue repo:beycom/onetool-mcp <keyword>Raise a new issue: github.com/beycom/onetool-mcp/issues/new
If you find OneTool useful:
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