feat: expose knowledge-base documentation through an MCP server
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@oto-macenauer-absa ya está trabajando en esto.
Desde el 4/10/2026.
- #119 de @oto-macenauer-absa — abierto
Evaluación
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Aptitud para principiantes
- 35/100
- Tipo de issue
- Nueva funcionalidad
- Claridad
- Bastante claro
- Estado de actividad
- Activo
- Stack tecnológico
- javascript
- Área
- api, documentation
Línea de trabajo
Start by locating the existing static build pipeline and the generated documentation data it produces. Then map the proposed MCP adapter over that catalog and search index; done means the listed resources, tools, schemas, bounded reads, deterministic search behavior, tests, and deployment documentation satisfy the acceptance criteria.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Feature Description
Provide an MCP server for the knowledge base so AI agents and other MCP-compatible clients can discover documentation and retrieve relevant documents without scraping rendered HTML.
The server should expose the documentation catalog as MCP Resources and provide agent-friendly discovery/search operations:
- List available documentation, with stable identifiers, title, app, description, tags, route, MIME type, and modification metadata.
- Search documentation by keyword and return ranked, bounded matches with excerpts and canonical document resource URIs.
- Allow clients to fetch a selected document through
resources/read.
Problem / Opportunity
The knowledge base aggregates documentation into a browser-oriented static site. Agentic clients need a protocol-native, structured interface for retrieval-augmented workflows: first discover/search available material, then fetch only relevant content.
A standard MCP surface makes this capability pluggable across compatible agents and clients, rather than coupling consumers to one UI, scraper, or proprietary API.
Acceptance Criteria
- An MCP server can be run/configured against a built knowledge-base deployment or its generated documentation index.
- Server advertises MCP
resourcesandtoolscapabilities. -
resources/listexposes a deterministic, paginated document catalog using stablekb://URIs. -
resources/readreturns requested document content and metadata for a catalog URI. - A
list_documentstool supports filtered catalog discovery (for example app, tag, or title). - A
search_documentstool accepts a keyword query and optional filters, pagination, and result limit. - Search results return deterministic ranking plus structured metadata: document URI, title, app/slug, route, excerpt, and relevance score.
- Tool outputs use JSON Schemas and return schema-valid structured content, with compatible text content where needed.
- Search and document reads enforce bounded response sizes and clear errors for unknown or inaccessible resources.
- Build/deployment produces required search/catalog data without runtime HTML scraping.
- Server validates inputs, applies access controls appropriate to deployment, rate-limits requests, and sanitizes returned content.
- Automated tests cover resource listing/reading, search ranking/filtering/pagination, schemas, deterministic ordering, and error handling.
- Documentation explains supported transport/configuration, MCP client setup, URI format, tool schemas, and security/operational limits.
Proposed Solution
Generate a normalized document catalog and search index during the existing static build pipeline. Implement a separate MCP adapter over that generated data so retrieval behavior stays independent from browser rendering and can be deployed or embedded using a supported MCP transport.
Use two complementary MCP primitives:
- Resources for canonical documents. Each document receives a stable
kb://URI, appears inresources/list, and is retrieved throughresources/read. - Tools for agent-directed discovery:
list_documentsfor filtered catalog enumeration.search_documentsfor ranked keyword search.
Search responses should return compact structured matches and resource links, enabling an agent to request full content only after selecting relevant results. Keep tool names server-namespaced and output schemas explicit to support aggregation with other MCP servers.
Evaluate whether resource-list change notifications should be enabled for deployments where documentation updates without server restart.
Dependencies / Related
- MCP Resources specification: https://modelcontextprotocol.io/specification/2026-07-28/server/resources
- MCP Tools specification: https://modelcontextprotocol.io/specification/2026-07-28/server/tools
- MCP architecture overview: https://modelcontextprotocol.io/docs/2026-07-28/learn/architecture
No existing MCP-related issue found in this repository.
Additional Context
Research findings:
- MCP Resources fit canonical documentation: clients can list resources, select them explicitly or automatically, and retrieve content by URI.
- MCP Tools fit parameterized search because keyword input, filters, ranking, and bounded result sets are actions rather than static documents.
- MCP requires deterministic list order and supports pagination/caching, useful for large documentation catalogs and agent prompt caching.
- Tool output schemas improve interoperability; structured search matches should be paired with readable text output for broad client compatibility.
- MCP security guidance requires input validation, access control, rate limiting, output sanitization, and client-side validation of untrusted tool results.
- Lenguaje dominante
- JavaScript
- Estrellas
- 0
- Forks
- 0
- Merge medio
- 20 min
- PR fusionados (30 d)
- 8
Preparar el entorno
- Incluye un Dockerfile o un archivo de Docker Compose
- Sin plantilla de pull request
- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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