Hi Eric,
I was not aware of SRU, thank you! This is very cool and useful.
Best,
*Thomas Scharff*
<https://library.wheatoncollege.edu/prf.php?account_id=205579> (he/him/his)
*Director of Discovery & Access*
Madeleine Clark Wallace Library <https://library.wheatoncollege.edu>, 125
Wheaton College <https://wheatoncollege.edu>
26 E. Main Street, Norton, MA 02766 <https://goo.gl/maps/d5JvoKZUEXy>
(508) 286-5601 <+15082865601>
On Mon, Oct 19, 2026 at 11:54 AM Eric Lease Morgan <
eric_morgan_at_infomotions.com> wrote:
> I created a Search/Retrieve via URL (SRU) interface that I'd like to share.
>
> As you may or may not know, SRU is a Web-based protocol designed to query
> bibliographic indexes, like library catalogs. [1] Over the past few years I
> have cached about 1.4 million open access articles and etexts. I used MARC
> to describe the cached items, and then I indexed and provided access to
> them via Koha. My Koha interface is simplistic. [2] I then turned on Koha's
> out-of-the-box SRU interface, and I had the interface's output enhanced
> with facets. The root of the interface is here: [3]
>
> I then spent time writing various SRU clients. One was a "thin" client,
> which eliminated my need to know SRU (or more specifically Context Query
> Language). It worked pretty well, but since search results included bunches
> o' links, and since Internet spiders found it, the spiders fell into
> infinite loops. I took down the thin client until further notice.
>
> Somewhere along the line I found a command-line client I wrote, which
> works pretty well too. [4] Given a query and an output directory, the
> client searches the catalog and downloads the full text of found items.
> Example usage includes:
>
> $ ./reader-sru-retrieve.py love ./love
> $ ./reader-sru-retrieve.py dc.author=plato ./plato
> $ ./reader-sru-retrieve.py '(dc.title=truth and dc.title=beauty)'
> ./truth-and-beauty
> $ ./reader-sru-retrieve.py '(dc.subject=covid and koha.ccode=cord)'
> ./covid
>
> Making it easy to download found items is very important to me. I think we
> -- us librarians -- ought to make it trivial to download the content from
> our collections. Click, save. Click, save. Click, save... Such is not easy
> nor scalable.
>
> I am currently working on an SRU via Model Context Protocol (MCP)
> interface, and it works even better, but the distribution s&cks. [5] More
> specifically, the MCP interface takes natural language commands as input,
> uses a large-language model (LLM) to transform the command into CQL,
> submits the query, gets back the results, the LLM interprets the results,
> and human language is returned to me. This eliminates my need to know what
> fields the SRU interface supports as well as eliminates my need to
> formulate complex Boolean queries. More importantly -- very importantly --
> the LLM analyzes the facets as well as the bibliographic results to create
> meaningful interpretations. Truly scalable, useful, and insightful. See,
> for example: [6]
>
> Fun with SRU.
>
>
> Links
>
> [1] SRU - https://www.loc.gov/standards/sru/
>
> [2] Koha interface - http://catalog.distantreader.org
>
> [3] SRU interface - http://catalog.distantreader.org:2100/biblios
>
> [4] SRU client - https://distantreader.org/tmp/reader-sru-retrieve.py
>
> [5] SRU via MCP - https://github.com/ericleasemorgan/reader-sru
>
> [6] MCP output - https://distantreader.org/tmp/sru-results.htm
>
> --
> Eric Morgan <eric_morgan_at_infomotions.com>
>
Received on Mon Oct 19 2026 - 12:00:14 EDT