Skip to main content
Glama
AI-Riksarkivet

Riksarkivet MCP Server

by AI-Riksarkivet
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: 'search_transcribed' is for discovering documents via keyword searches, while 'browse_document' is for retrieving full transcriptions of specific pages. There is no overlap or ambiguity between them; each serves a different stage in the document exploration workflow.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern ('search_transcribed' and 'browse_document'), using snake_case throughout. The verbs 'search' and 'browse' accurately reflect their distinct functions, and the pattern is uniform across the tool set.

    Tool Count2/5

    With only two tools, the server feels under-scoped for its domain of historical document exploration. While the tools cover search and viewing, there are likely missing operations such as filtering by metadata, listing document collections, or handling user sessions. A typical server in this domain would benefit from 5-10 tools for a more complete surface.

    Completeness3/5

    The server provides core search and browse functionality, but there are notable gaps. It lacks tools for document metadata retrieval, collection browsing, or advanced filtering beyond keyword search. Agents can work around this by using the existing tools iteratively, but the surface is incomplete for comprehensive historical research workflows.

  • Average 4.7/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 7 of 7 community issues answered or closed in the last 6 months
    • 144 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it retrieves transcriptions in Swedish, includes links to original images and ALTO XML, supports various page specifications, and notes transcriptions are as they appear historically. It lacks details on rate limits or error handling, but covers core operational traits well.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is front-loaded with core purpose but includes verbose sections like 'Key features' and 'Examples' that repeat information. Sentences like 'Download some of the nearby pages too...' are ambiguous and could be trimmed. It's informative but not optimally concise, with some redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given 4 parameters with 0% schema coverage, no annotations, but an output schema exists, the description does well. It covers purpose, usage, parameters, and examples thoroughly. The output schema likely handles return values, so the description appropriately focuses on input and behavior. Minor gaps in error handling or limits keep it from a perfect score.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description must fully compensate. It provides detailed semantics for all parameters: explains 'reference_code' format with examples, describes 'pages' syntax for single/range/multiple, clarifies 'highlight_term' as optional keyword highlighting, and specifies 'max_pages' default and purpose. This adds substantial value beyond the bare schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Browse specific pages of a document by reference code and view full transcriptions.' It specifies the verb ('browse'), resource ('document pages'), and distinguishes from the sibling tool 'search_transcribed' by emphasizing complete page content rather than search snippets.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit guidance on when to use this tool: 'Use this tool when you need complete page content rather than just search snippets.' This directly contrasts with the sibling tool 'search_transcribed' (implied to provide snippets), offering clear alternatives and context for selection.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It explains the search capabilities (Solr query syntax), return format (document metadata, page numbers, text snippets), pagination behavior, and provides extensive examples and troubleshooting guidance for effective use.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    While the description is comprehensive and well-structured with clear sections, it is extremely lengthy with extensive examples, troubleshooting tips, and advanced strategies that could be condensed. The core information is front-loaded, but the overall length exceeds what's typically needed for effective tool selection.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the complexity of the search functionality, 0% schema description coverage, no annotations, and the presence of an output schema, the description provides complete contextual information. It covers purpose, usage, parameters, behavioral characteristics, examples, troubleshooting, and integration with sibling tools, making it fully self-contained for an AI agent.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all parameters. It explains 'keyword' supports advanced Solr syntax with extensive examples, 'offset' for pagination with specific increments, and provides default values and usage guidance for all other parameters in the 'Best practices' section.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool searches for keywords in transcribed historical documents from the Swedish National Archives, specifying it returns matching pages with transcriptions. It distinguishes from the sibling 'browse_document' tool by focusing on search functionality rather than viewing full transcriptions.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit guidance on when to use this tool vs alternatives, mentioning to use 'browse_document tool to view full page transcriptions of interesting results.' It also includes troubleshooting tips and advanced strategy sections that guide users on effective usage patterns.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

ra-mcp MCP server

Copy to your README.md:

Score Badge

ra-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AI-Riksarkivet/ra-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server