mcp server
io.github.bytedance/mcp-server-search
MCP server for web search operations
Description as published by the maintainer. Source
- version 1.0.0
- active
- retrieval
active — Most recent push to the repository was 2026-08-05. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 38,475 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-05 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 415 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2025-09-09 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | Apache-2.0 | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2025-09-09 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
io.github.bytedance/mcp-server-browser
— last commit 2026-08-05, shares agent, agent-tars, browser-use
MCP server for browser use access
-
io.github.bytedance/mcp-server-commands
— last commit 2026-08-05, shares agent, agent-tars, browser-use
An MCP server to run arbitrary commands
-
io.github.bytedance/mcp-server-filesystem
— last commit 2026-08-05, shares agent, agent-tars, browser-use
MCP server for filesystem access
-
Optical Context MCP
— last commit 2026-04-04, shares multimodal, vision
Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.
-
com.browser-use/browser-use
— last commit 2026-08-05, shares browser-use
Control a real Chrome browser to complete any task: fill forms, extract data, book flights.
-
io.github.Daichi-Kudo/llm-advisor
— last commit 2026-06-18, shares vlm
Real-time LLM/VLM benchmarks, pricing, and recommendations. 300+ models, 5 sources.
-
Contendeo
— last commit 2026-04-24, shares multimodal
Multimodal video analysis MCP — transcription, vision, and OCR for any video URL.
-
io.github.DustinTrap/kvm-pilot
— last commit 2026-08-05, shares vision
Smart hands for your AI agents - write-capable KVM+BMC+SSH MCP server: gated, verified, audited.
-
Glasswarp
— last commit 2026-08-01, shares computer-use
Eyes and hands on real Windows PCs — observe, click, type via Glasswarp API.
-
io.github.antbotlab/mac-use-mcp
— last commit 2026-05-01, shares computer-use
Zero-dependency macOS desktop automation for AI agents. 18 tools via MCP. macOS 13+.
These share tags the maintainers applied themselves, such as agent, agent-tars, browser-use, computer-use. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: agent, agent-tars, browser-use, computer-use, cowork, gui-agent, gui-operator, mcp, mcp-server, multimodal, tars, ui-tars, vision, vlm.
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
Join ZBS AI Practice Lab