Data Sources & Coverage
ra-mcp connects to several Riksarkivet APIs:
| API | Endpoint | Purpose |
|---|---|---|
| Search API | data.riksarkivet.se/api/records |
Full-text search across transcribed documents |
| ALTO XML | sok.riksarkivet.se/dokument/alto |
Structured page transcriptions with text coordinates |
| IIIF | lbiiif.riksarkivet.se |
High-resolution document images and collection manifests |
| OAI-PMH | oai-pmh.riksarkivet.se/OAI |
Document metadata and collection structure |
| Bildvisaren | sok.riksarkivet.se/bildvisning |
Interactive image viewer (links provided in results) |
All data comes from the Riksarkivet Data Platform, which hosts AI-transcribed materials from the Swedish National Archives.
Additional resources: Förvaltningshistorik (semantic search, experimental), HTRflow (handwritten text recognition).
Archive Coverage
The archive has three access tiers — not all materials are searchable the same way:
| Tier | Tool | Coverage |
|---|---|---|
| Metadata catalog | search_metadata |
2M+ records — titles, names, places, dates |
| Digitised images | browse_document (links) |
~73M pages viewable via bildvisaren |
| AI-transcribed text | search_transcribed |
~1.6M pages — currently court records (hovrätt, trolldomskommissionen, poliskammare, magistrat) from 17th-18th centuries |
Church records, estate inventories, and military records are typically cataloged and often digitised, but NOT AI-transcribed.
Transcription Quality
The AI-transcribed text was produced by HTR (Handwritten Text Recognition) and OCR models. These transcriptions are not perfect — they contain recognition errors including misread characters, merged or split words, and garbled passages, especially in older or damaged documents.
This has a direct impact on search: an exact search for Stockholm will miss documents where the transcription reads Stockholn or Stookholm due to recognition errors. Always use fuzzy search (~) to compensate — stockholm~1 catches common misreads and significantly increases the number of hits.
The Plugin Model
ra-mcp is one piece of a larger ecosystem. Multiple MCP servers can be connected to the same AI client:
graph LR
client["AI Client\n(Claude)"]
client --> ramcp["ra-mcp\nSearch, browse, HTR, viewer, guides"]
client --> htrflow["htrflow-mcp\nStandalone HTR\n(alternative)"]
client --> other["other servers\nAny MCP-compatible tool"]Together with external tools, they enable a complete research workflow: search the archives, read transcriptions, re-transcribe pages that need better OCR/HTR, and view original documents — all from within a single AI conversation.