Context7
by upstash
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Computer or cloud★ 64,224MITUpdated yesterday
Install
Tool Search Proxy
Overview
Description from the maker (original English)
Lets a model search and call a large MCP tool catalog through five tools instead of loading it
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: Streamable HTTP, stdio
- Category: Search & AI memory
- You need to fill in: MCP_TRANSPORT, TOOLSEARCH_UPSTREAM
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- You fill in yourself:
MCP_TRANSPORT,TOOLSEARCH_UPSTREAM,TOOLSEARCH_EMBEDDER
You need
- DockerDocker installed
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"toolsearch-proxy": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"TOOLSEARCH_UPSTREAM",
"-e",
"TOOLSEARCH_EMBEDDER",
"ghcr.io/datolabs-io/mcp-toolsearch-proxy:0.9.0"
],
"env": {
"MCP_TRANSPORT": "your-value",
"TOOLSEARCH_UPSTREAM": "your-value",
"TOOLSEARCH_EMBEDDER": "your-value"
}
}
}
}Run this in your terminal
claude mcp add toolsearch-proxy --env MCP_TRANSPORT=your-value --env TOOLSEARCH_UPSTREAM=your-value --env TOOLSEARCH_EMBEDDER=your-value -- docker run -i --rm -e MCP_TRANSPORT -e TOOLSEARCH_UPSTREAM -e TOOLSEARCH_EMBEDDER ghcr.io/datolabs-io/mcp-toolsearch-proxy:0.9.0Fill in the empty values before running it.
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"toolsearch-proxy": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"TOOLSEARCH_UPSTREAM",
"-e",
"TOOLSEARCH_EMBEDDER",
"ghcr.io/datolabs-io/mcp-toolsearch-proxy:0.9.0"
],
"env": {
"MCP_TRANSPORT": "your-value",
"TOOLSEARCH_UPSTREAM": "your-value",
"TOOLSEARCH_EMBEDDER": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"toolsearch-proxy": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"TOOLSEARCH_UPSTREAM",
"-e",
"TOOLSEARCH_EMBEDDER",
"ghcr.io/datolabs-io/mcp-toolsearch-proxy:0.9.0"
],
"env": {
"MCP_TRANSPORT": "your-value",
"TOOLSEARCH_UPSTREAM": "your-value",
"TOOLSEARCH_EMBEDDER": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
Values you fill in
- stdio: MCP on standard input and output. Upstream requests then carry no token, so this suits only an upstream that needs no authentication
- Streamable HTTP URL of an MCP server that needs no authentication
TOOLSEARCH_EMBEDDERenvbuiltin for semantic search, which needs the model in a volume at /model (see docs/deploy.md); none for lexical search only
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account datolabs-io, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7264 servers in this category
- Published to the registry more recently than 91% of the other 7264 servers in this category
- Basic checks equal to or better than 100% of the other 7264 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Tool Search Proxy safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
You need to fill in: MCP_TRANSPORT, TOOLSEARCH_UPSTREAM
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.9.0) reached the registry 3 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
What can I use instead?
In the same category: Context7, Codebase Memory, Exa
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Codebase Memory
by DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Runs on your computer★ 48,148MITUpdated 21 days ago
Install
Exa
by exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Runs in the cloud★ 5,213MITUpdated last month
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
mcp-toolsearch-proxy
mcp-toolsearch-proxy lets a model use hundreds or thousands of MCP tools without loading them. On 500 tools, each request carries 97% fewer tokens of tool definitions, a task costs about half as much, and the model reaches the right tool nearly as often as with every tool loaded (benchmarks).
It is an MCP server that puts five tools in front of an MCP server with far too many to list to a model, such as a gateway that aggregates dozens of servers:
| Tool | Does |
|---|---|
search_tools | finds the tools that can do what a query describes, with the input schemas of the best few, for up to 5 queries at once; with the built-in model, in English, Lithuanian or any of 100 other languages |
describe_tool | returns the full description and input schema of up to 10 tools |
call_read_tool | calls a tool the upstream marks read-only, and refuses any other |
call_read_tools | calls up to 10 read-only tools at once, in parallel, with a result for each (-max-batch-calls; 0 leaves it out) |
call_write_tool | calls any tool, for those that may create, change or delete something |
A catalog of a thousand tools costs a model over 100,000 tokens of tool definitions before it does anything, and many clients cap how many tools they load anyway. Behind the proxy, the model sees five, in 1,735 tokens.
A call whose arguments do not fit the tool's input schema (a required property missing, a wrong type, a value outside an enum) is refused before it reaches the upstream, with what is wrong and the schema, so the model can fix it at once. The same goes for an unknown name that is clearly a typo of one tool, and for an upstream that answers invalid params.
Calls come in separate tools so that a client can tell them apart: call_read_tool and call_read_tools are marked read-only and can be allowed to run without asking, while call_write_tool is marked destructive and can keep asking every time. Writes are never batched, so each keeps its own approval. A tool counts as read-only only when the upstream server marks it so (readOnlyHint); unmarked tools are writes, and so are any the operator lists in -write-tools. Allowing call_read_tool allows every read-only tool of every server behind the upstream, including servers added later; docs/clients.md says what that grant covers and how to set up claude.ai and Claude Code.
client ──▶ gateway /mcp/search ──▶ mcp-toolsearch-proxy ──▶ gateway /mcp/all ──▶ MCP serversHow it works
The proxy has no credentials. Each request it sends upstream carries the caller's Authorization header and nothing else, so the upstream server (usually the same gateway, on another route) authenticates and authorizes the caller as if they had come directly. Whatever the caller isn't allowed to see or call, the proxy can't see or call either.
Each caller gets their own catalog: the tools the upstream lists for that caller. It is kept for ten minutes, then listed again in the background while the old one is still used, and it is looked up by a hash of the token. A claim inside the token, such as sub, would be easier to key on but can't be trusted without verifying the token, so the proxy doesn't use one.
Search combines two rankings. BM25 matches words in tool names, descriptions and parameters, with Lithuanian and English endings stemmed and diacritics ignored. A multilingual embedding model, potion-multilingual-128M (MIT), matches by meaning. The model runs inside the proxy, in pure Go, without a GPU or an embedding service, and embedding a query takes microseconds. Without the model, search falls back to BM25 alone, which matches only words a tool's text shares with the query: it stems no endings but Lithuanian and English ones, and does not split Chinese or Japanese text into words.
The upstream server's own instructions still reach the model. The proxy answers each caller's handshake with its own short guidance followed by the upstream's instructions, unchanged, as the caller's catalog received them, up to -max-instructions characters (10,000 by default; longer ones are cut, with a note saying so). Clients cut it again, much sooner: Claude Code keeps about 4,000 characters of a server's instructions, so only the start of a long upstream text reaches the model (see docs/clients.md). And search_tools returns the input schemas of its best few matches (-search-schemas, 3 by default), so a call usually follows a search directly.
Logs and metrics record tool names, outcomes and timings. Queries, arguments, results and tokens never appear in them; docs/privacy.md has the details. The transport is streamable HTTP without sessions, for MCP 2026-07-28 clients and older ones, so a restart or a load balancer doesn't break a client's connection. -transport stdio serves the same tools on standard input and output instead, for clients that start servers as local commands. There is no caller's token there, and the proxy has none of its own, so stdio works only with an upstream that needs no authentication (docs/clients.md).
It works with any upstream that speaks streamable HTTP MCP and authorizes by bearer token. docs/agentgateway.md shows a complete agentgateway setup, which the end-to-end tests run.
Status
Early development. The tools, their arguments and the settings may still change before 1.0.
Install
Homebrew, on macOS or Linux:
brew install --cask datolabs-io/tap/mcp-toolsearch-proxyPackages (.deb, .rpm), archives and a container image are attached to each release. See docs/deploy.md.
mcp-toolsearch-proxy fetch-model -model-dir ./model # once: ~530 MB, checked against pinned digestsmcp-toolsearch-proxy -upstream https://gateway.example.com/mcp/all -model-dir ./model
-embedder none skips the model and searches lexically only. docs/configuration.md lists every setting, as mcp-toolsearch-proxy -h does; each has an environment variable too. Then connect a client: docs/clients.md.
Clients that already defer MCP tools and search them on demand, as Claude Code does, gain less from the proxy; see when you don't need this.
Search quality
The repository holds an evaluation set of made-up tools, described in English, and questions people ask about them in English and Lithuanian. Recall at 5 today:
| Search | English | Lithuanian |
|---|---|---|
lexical only (-embedder none) | 52% | 0% |
| hybrid with the built-in model | 81% | 79% |
Words alone can't connect a Lithuanian question to an English description. The model can. Tests hold changes to ranking to these numbers.
Benchmarks
On a made-up catalog of 500 tools, a model given 30 questions reaches the right tool nearly as often through the proxy (90%) as with every tool loaded (95%), at about half the cost per task, and more often than with Anthropic's tool search (87%). docs/benchmarks.md has the numbers, what a client loads in each mode at up to 1,490 tools, and how to run the benchmarks.
Development
mise install # the pinned toolchain and the git hooksmise run ci # lint, scan and unit tests, as CI runs them mise run test:model # the built-in model against its reference implementation and the evaluation set mise run e2e:up # agentgateway, the proxy and fixture MCP servers, with Docker Compose mise run test:e2e # the end-to-end tests, against that stack or any at E2E_SEARCH_URL and E2E_ALL_URL mise run docs:config # regenerate docs/configuration.md after changing a flag
See CONTRIBUTING.md and ARCHITECTURE.md.
Licence
MIT. The built-in model is published by Minish under the MIT licence and is downloaded, not distributed, by this project.