Ohi, I'm the original creator of Searx, but due to the limitations of the metasearch concept I'm not involved in the development anymore. My new search project is https://github.com/asciimoo/hister (https://hister.org/).
Hister is a full text indexer for websites and local files which automatically saves all the visited pages rendered by your browser. Storing full page content allows serving offline result previews and the full page content via MCP.
Hister is a great idea and the creator is a really nice person, please give it an honest look and consider supporting them (I'm Uruky's co-founder and we sponsored them)!
I'm sorry for not taking the time to read the docs, but I have a question.
Some 20 years ago a friend of mine has set up a local proxy (python if I'm not mistaken) that was gathering all his web traffic and served him as a long term memory. The proxy had a web interface and allowed him to quickly find something he saw ca. 10 days ago, or that specific algorithm he recalls but can't remember it's name.
For years I've been collecting links to different work related trivia which I use on a daily basis as a rabbit-from-a-hat solution to answer random question from friends and coworkers. For example someone randomly asked me for an idea for color palette for data charts and I can immediately give them a scientific research into the color palette. Or an obscure algorithm.
But with time the collection has grown substantially and it's really cumbersome to find the proper things.
Absolutely, this is a great example where Hister can shine.
I started Hister as a proxy as well, but quickly switched to the current extension based approach, because intercepting HTTPS traffic requires a MiTM proxy which is much more painful to setup than installing a browser extension.
would it be possible to gdrive/rsync/git the data between machines and then use the data on an online server for retrieval (given that I would handle data sync myself)?
also what exactly are you using for search? does it support trigrams? how do you sort results?
I found Hister a few month ago and was amazed by it.
Now for many of us the browser extension approach is not possible (mobile usage, security, etc.)
My feeling is for a lot of users there is really a third way apart from the MiTM proxy or Browser extension approach. I actually do not want my "personal" / "logged in" pages to be indexed. This is a bit like the MS recall nightmare (self hosted version).
Any way to get the list of URL visited (with something like Privoxy, or maybe one of those popular ad blockers like Pi Hole but I guess they just get DNS queries?) and then importing it with some filtering rules with a nightly batch job is good enough for a lot of people.
The browser import [1] is great but I guess hard to use with mobile...
Also very interested in this. I was playing around with doing the same thing with YaCY. I want the proxy aspect so that I can proxy my phone traffic through it as well.
YaCY has a proxy mode that automatically index your web-serving. In my experience, the index grow in size very fast and reaches ~100GB or more. How does the index size of Hister compare to that?
Hister stores only the text content of HTML/pdf pages. 1000 documents require around 80-100MB of storage and there is still plenty of room to optimize for storage space.
I'm using it for 6-7 months and my index size is below 1GB with almost 10k pages.
Also, a downside of the proxy approach: it does not handle properly JS based websites and cannot identify dynamic content changes. Our extension periodically checks if the browser tabs' content has been changed and automatically updates the index when change detected.
Hister sounds like something I wanted for a while, but never got around to building. Searching stuff I’ve seen before is most of what I do with a search engine, so having it local and fast would be amazing. Eager to give it a try.
Always excited to see new things like Hister in the search space. What are the scaling limits, as far as you can tell in terms of how much can it hold before queries start breaking down or become too slow to be useful? Could it evolve into a general internet search engine if, say, enough trusted members of a geo-distributed YugabyteDB cluster and an army of crawlers built a sufficient index?
> What are the scaling limits, as far as you can tell in terms of how much can it hold before queries start breaking down or become too slow to be useful?
There has been no stress tests in this regard. The indexer lib Bleve [1] can handle millions of documents according to their documentation.
> Could it evolve into a general internet search engine if, say, enough trusted members of a geo-distributed YugabyteDB cluster and an army of crawlers built a sufficient index?
My long term goal is exactly this. I'd like to add federation/P2P feature [2][3] to evolve from being a private search companion. I'd appreciate any help designing the system.
This is great, like many others I've been thinking of something like hister but only for bookmarked web pages. I presume it should be straightforward with hister to do that?
It is possible. The automatic website indexing can be turned off in the extension and manual indexing can be triggered via the command line tool, the extension popoup or by hotkeys.
Wow! that looks like a bit of software I have been dreaming about for awhile - will definately check out! You're at least doing something right in communicating the reasons why and appeal for starters! All the best!
I love your idea and wondered why saving and indexing browser visited pages was not being done. Does this handle large amounts of local files, for example 10-20TB across file types like Powerpoint, Excel, Word, and PDF?
In its current form it cannot handle this amount of data efficiently (and doesn't support powerpoint/excel/word yet), but this is a valid use-case, I've added a TODO item to experiment with it.
Both are search engines, but that's all the similarity. Hister has a traditional crawler, but its biggest strength is automatically indexing browser tabs as those are rendered. This way it bypasses authentication, CloudFlare, captchas and most of the annoying limitations of traditional crawlers.
Hister also provides full offline result previews. Check out the small read-only demo: https://demo.hister.org/
I was considering paying someone to build something like this at some point. With two jobs, I eventually had no time to even organize what I find. It's just piles of links in text files.
Can I give your software a huge list of URL's to index? Or do I need to use browser automation to open them a few at a time with it caching and indexing them?
Hister has a built in crawler with standard HTTP lib and browser based backends, you can feed your link collection to it. Also, Hister supports importing your existing browser history automatically using either of the mentioned backends.
I installed this a while back and honestly I almost never touch it. It turns out that for me searching my history doesn't really replace a search engine at all. The built in extractor list is pretty limited and adding them seems like too much of an ordeal for me to bother.
Sure, it cannot fully replace web search engines (yet), but it can reduce the dependence on these services more and more as your index grows. Hister is designed to support quickly falling back to traditional search engines with a single hotkey if no results found.
I agree, we should add more extractors [1]. Can you recommend extractors you missed?
SearXNG is my daily internet search now +5 years; with YaCY Backends and else as fallback. I also build internal document search or RAG applications with this setup (SearXNG also support json results).
However, there are some downer I accept because of privacy:
1. Its slower and the results are not that good then with others. But fast and good enough for most of my queries.
2. From time to time you get blocked on the duckduckgo, brave or whatever search and you must solve some captures. You can prevent this by getting and using API-Keys from them.
The nice thing about using your own backend is, that you can prio it in the results and for example, if I crawl the smallweb and other site important for myself, this sites come up first in the results.
> SearXNG is my daily internet search now +5 years
Same here
> with YaCY Backends and else as fallback.
Do you run your own "super fast" YaCy instance? or with specific settings?
My experience with YaCy is it doesn't fit in the backend of SearX since YaCy kind of slowly stream results for about 30 seconds...
I also have a local `kiwix-serve` serving ZIM files of wikipedia, wiktionary, gutemberg, archwiki, etc. but same problem the kiwix search engine [0] doesn't really fit as a backend for SearX as it returns too many results and pollute the SearX result page.
What I haven't done yet is trying to plug SearX to a local Recoll instance [1]. But Recoll doesn't support indexing ZIM files... but could be useful for other archived html documents.
I would be curious to know more about a working setup since search is hard to get right.
I ran my own YaCY instances. Three of them to be specific, because they are "super fast" and "reboot" often. I crawl with them the smallweb, smallcomic and smallyt sites and also all feeds from my miniflux instance; getting them via the miniflux api. Beside that i have other static entries that i crawl.
For wikibooks and wikipedia i tried and use also YaCY, but it use a lot of resources. So its only in one instance. I suggest >16GB RAM and 300GB+ HDD if you want to do this.
To access wikimedia, gutemberg, archwiki or media.ccc.de directly, I use also SearXNG.
Usually it takes 1-3 Seconds to get search results from YaCY in my setup.
I run them in docker on aarch64 with ~6GB of RAM and 200GB HDD. The VPS it-self has 8GB RAM, 6 arm cores and 250GB HDD. If YaCY hang, i just restart it.
This are my pretty good working docker deploy and java settings I use currently:
That's the smallest I got it running mostly stable and self-healing with a index size of +100GB. I also avoid to use crawling by the build in tasks and use the API and cron jobs for weekly feed importing, because I found out, that kind of crawling eats up less resources then the usual. All-Over, to much running crawlers, make retrieving search results slow.
For production use, I suggest to min. double the resources. If you do this, it becomes very stable.
I've been using searxng for several years now. I don't run my own instances because the inhumane network censorship imposed by GFW, and proxy detection enforced by search engines. Instead, I rely on public instances on the list [1] and libredirect [2]. Note that service from a single instance is not guaranteed, but you can always switch to other available instances with little cost within a minute.
I won't say searxng can help you degoogle because metasearch engine calls other search engines, e.g., google, to collect results. However, if you try searxng, you can at least get rid of things like ai reviews in no time.
In the end, thank you people after searxng project and public instances.
I built something similar ([1]) that you might find interesting. Similar to your project, but with the fun tweak that it bundles searxng inside itself, so you don't need to run or find a searxng instance to use it.
It has a JSON mode that you need to enable in settings and then you can create a simple python script to interact with it or have the agent use `curl` and `jq` to interact with it.
I am also interested in what a full local AI stack with web search and other tools looks like. As far as I can tell, SearX does not embed an MCP server, so it can't be directly called from llama-server for example. Open WebUI does have an integration for SearX and other providers, but the results I obtained weren't particularly impressive.
I use Searxng through Onyx, both as regular search and Onyx's Deep Research mode. I also have https://github.com/ihor-sokoliuk/mcp-searxng to add search to coding agents. Haven't really had many issues with it.
i have a friend with a 4080 that is wanting to experiment with local models and those cards should be similar enough. can you give any more detail about your setup? ty!
It is really great to use. As the poster above mentioned, my setup with Sear is the following, all through `llama.cpp`, which has a built-in webui with an MCP client:
* SearXNG in Docker — enable the JSON API (`search.formats: [html, json]`; off by default).
* `llama-server` with `--webui-mcp-proxy`, then add the server in the webui.
Some gotchas:
* `searxng-mcp` forgets to declare its own dep → `--with fastmcp`.
* Endpoint is `/mcp`, not the `/searxng-mcp/mcp` the docs claim.
* `--webui-mcp-proxy` only enables the CORS proxy; each MCP server entry still needs its "Use llama-server proxy" checkbox ticked, or the browser fetches direct and CORS-fails.
* Terminal clients (OpenCode etc.) skip the proxy — point them straight at `:8100/mcp`.
A couple interesting tidbits:
* There are temporal issues with search-related tool calls. The model trips out. 2026 results read to it a "future-dated hallucination" because it doesn't know the date. There's an additional `--tools get_datetime` function that will allow it to ground via the real date.
* Snippets-only is enough for most "what's current" questions and keeps context tiny.
I’ll have to try, I’ve only recently learned Exa pricing is a bit crazy (especially on searches where you source 30-40 sources)I just used it be default and then was like oh damn when I got hit
TinySearch wraps this and works well for agents. It's better than the native SearXNG MCP because it optimizes the context before it even gets to the agent so as to not waste tokens.
I’ve been a big fan of SearXNG for a while now. My distain for google has only grown, so having the ability to search and avoid things like yk, small AI models being installed on my PC without my consent, is awesome.
I've been using SearXNG for a few years now, however I've been trying out Degoog as a SearXNG alternative since I've had issues with engines constantly failing or being slow since day 1 of using SearXNG, but Degoog has worse results with the same engines. It's a shame since I'm having to pick between slower but better results, or very fast but worse results.
I've been using this for some projects. It's exceptional and I recommend it highly.
I actually included a recipe to deploy it to kubernetes in typekro, my TypeScript infrastructure-as-code project for kubernetes: https://typekro.run/api/searxng/
Yeah, I find that searx results are way more relevant to what I’m actually looking for than a single engine. There’s so much manipulation going on that if you don’t aggregate multiple engines, it’s near impossible to get what you want.
Highly recommend this. I set up a self-hosted instance and been using it exclusively for months. It's better than DDG and i don't miss Google whatsoever.
Image search is worse i guess mostly for lack of CDN so it's slow but whatever.
Hister is a full text indexer for websites and local files which automatically saves all the visited pages rendered by your browser. Storing full page content allows serving offline result previews and the full page content via MCP.
Take a look at how the MCP can be utilized: https://hister.org/posts/give-your-ai-assistant-a-private-me...
Some 20 years ago a friend of mine has set up a local proxy (python if I'm not mistaken) that was gathering all his web traffic and served him as a long term memory. The proxy had a web interface and allowed him to quickly find something he saw ca. 10 days ago, or that specific algorithm he recalls but can't remember it's name.
For years I've been collecting links to different work related trivia which I use on a daily basis as a rabbit-from-a-hat solution to answer random question from friends and coworkers. For example someone randomly asked me for an idea for color palette for data charts and I can immediately give them a scientific research into the color palette. Or an obscure algorithm.
But with time the collection has grown substantially and it's really cumbersome to find the proper things.
Would your project be a good fit for my problem?
I started Hister as a proxy as well, but quickly switched to the current extension based approach, because intercepting HTTPS traffic requires a MiTM proxy which is much more painful to setup than installing a browser extension.
also what exactly are you using for search? does it support trigrams? how do you sort results?
Now for many of us the browser extension approach is not possible (mobile usage, security, etc.)
My feeling is for a lot of users there is really a third way apart from the MiTM proxy or Browser extension approach. I actually do not want my "personal" / "logged in" pages to be indexed. This is a bit like the MS recall nightmare (self hosted version).
Any way to get the list of URL visited (with something like Privoxy, or maybe one of those popular ad blockers like Pi Hole but I guess they just get DNS queries?) and then importing it with some filtering rules with a nightly batch job is good enough for a lot of people.
The browser import [1] is great but I guess hard to use with mobile...
- [0] https://www.privoxy.org/
- [1] https://hister.org/docs/importing-browser-history
There is already an ongoing discussion about the topic: https://github.com/asciimoo/hister/issues/387
The currently discussed solution relies on the browser extension, but mobile Firefox has extension support.
I'm using it for 6-7 months and my index size is below 1GB with almost 10k pages.
Also, a downside of the proxy approach: it does not handle properly JS based websites and cannot identify dynamic content changes. Our extension periodically checks if the browser tabs' content has been changed and automatically updates the index when change detected.
There has been no stress tests in this regard. The indexer lib Bleve [1] can handle millions of documents according to their documentation.
> Could it evolve into a general internet search engine if, say, enough trusted members of a geo-distributed YugabyteDB cluster and an army of crawlers built a sufficient index?
My long term goal is exactly this. I'd like to add federation/P2P feature [2][3] to evolve from being a private search companion. I'd appreciate any help designing the system.
[1] https://blevesearch.com/docs/Home/ [2] https://github.com/asciimoo/hister/discussions/432 [3] https://hister.org/posts/public-search
All the best!
Can I give your software a huge list of URL's to index? Or do I need to use browser automation to open them a few at a time with it caching and indexing them?
Hister has a built in crawler with standard HTTP lib and browser based backends, you can feed your link collection to it. Also, Hister supports importing your existing browser history automatically using either of the mentioned backends.
I agree, we should add more extractors [1]. Can you recommend extractors you missed?
[1] https://github.com/asciimoo/hister/issues/305
The nice thing about using your own backend is, that you can prio it in the results and for example, if I crawl the smallweb and other site important for myself, this sites come up first in the results.
Same here
> with YaCY Backends and else as fallback.
Do you run your own "super fast" YaCy instance? or with specific settings?
My experience with YaCy is it doesn't fit in the backend of SearX since YaCy kind of slowly stream results for about 30 seconds...
I also have a local `kiwix-serve` serving ZIM files of wikipedia, wiktionary, gutemberg, archwiki, etc. but same problem the kiwix search engine [0] doesn't really fit as a backend for SearX as it returns too many results and pollute the SearX result page.
What I haven't done yet is trying to plug SearX to a local Recoll instance [1]. But Recoll doesn't support indexing ZIM files... but could be useful for other archived html documents.
I would be curious to know more about a working setup since search is hard to get right.
- [0] https://kiwix-tools.readthedocs.io/en/latest/kiwix-serve.htm...
- [1] https://docs.searxng.org/dev/engines/online/recoll.html
Thanks to pointing out kiwix. I'll give it a try.
I won't say searxng can help you degoogle because metasearch engine calls other search engines, e.g., google, to collect results. However, if you try searxng, you can at least get rid of things like ai reviews in no time.
In the end, thank you people after searxng project and public instances.
[1] https://searx.space
[2] https://github.com/libredirect/browser_extension
It also needs a SearXNG server to run, so I recently pivoted towards a self-contained solution: https://github.com/denysvitali/search-mcp
[1]: https://github.com/nikvdp/searxng-ai-kit
I'm curious what setups folks use to provide this functionality.
Since the quantized 24B parameter Gemma model came out, I've had good luck with tool calling on a 4070 Ti Super.
Successful tool calling is what finally made the local experience useful.
I should note this is for the general and not coding specific context.
It's at the bottom of this page: https://docs.searxng.org/admin/settings/settings_search.html
i have a friend with a 4080 that is wanting to experiment with local models and those cards should be similar enough. can you give any more detail about your setup? ty!
`gemma4-26b-a4b-it-qat.gguf`
https://huggingface.co/lmstudio-community/gemma-4-26B-A4B-it...
It is really great to use. As the poster above mentioned, my setup with Sear is the following, all through `llama.cpp`, which has a built-in webui with an MCP client:
* SearXNG in Docker — enable the JSON API (`search.formats: [html, json]`; off by default).
* `searxng-mcp` (FastMCP, native streamable-HTTP): `TRANSPORT=streamable-http HOST=127.0.0.1 PORT=8100` `SEARXNG_URL=http://localhost:8888 uvx --from searxng-mcp --with fastmcp searxng-mcp`
* `llama-server` with `--webui-mcp-proxy`, then add the server in the webui.
Some gotchas:
* `searxng-mcp` forgets to declare its own dep → `--with fastmcp`.
* Endpoint is `/mcp`, not the `/searxng-mcp/mcp` the docs claim.
* `--webui-mcp-proxy` only enables the CORS proxy; each MCP server entry still needs its "Use llama-server proxy" checkbox ticked, or the browser fetches direct and CORS-fails.
* Terminal clients (OpenCode etc.) skip the proxy — point them straight at `:8100/mcp`.
A couple interesting tidbits:
* There are temporal issues with search-related tool calls. The model trips out. 2026 results read to it a "future-dated hallucination" because it doesn't know the date. There's an additional `--tools get_datetime` function that will allow it to ground via the real date.
* Snippets-only is enough for most "what's current" questions and keeps context tiny.
Let me know if you have any questions!
https://github.com/MarcellM01/TinySearch
I actually included a recipe to deploy it to kubernetes in typekro, my TypeScript infrastructure-as-code project for kubernetes: https://typekro.run/api/searxng/
Image search is worse i guess mostly for lack of CDN so it's slow but whatever.