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Glama
shenyimings

DocNav-MCP

by shenyimings
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
load_documentB

Load a document for navigation and analysis.

Args:
    file_path: Path to the document file

Returns:
    Success message with auto-generated document ID
get_outlineA

Get document outline/table of contents.

Tips: First use this tool to understand document structure after you load a document.

Args:
    doc_id: Document identifier
    max_depth: Maximum heading depth to include, defaults to 3

Returns:
    Formatted document outline
read_sectionA

Read content of a specific document section.

Args:
    doc_id: Document identifier
    section_id: Section ID from outline (e.g., 'h1_0', 'h2_1')

Returns:
    Section content with subsections
search_documentC

Search for specific content within a document.

Args:
    doc_id: Document identifier
    query: Search term or phrase

Returns:
    Formatted search results with context
navigate_sectionC

Get navigation context for a section (parent, siblings, children).

Args:
    doc_id: Document identifier
    section_id: Section ID to navigate to

Returns:
    Navigation context with related sections
list_documentsA

List all currently loaded documents.

Returns:
    List of loaded documents with their metadata
get_document_statsC

Get statistics about a loaded document.

Args:
    doc_id: Document identifier

Returns:
    Document statistics and structure info
remove_documentC

Remove a document from the navigator.

Args:
    doc_id: Document identifier (UUID)

Returns:
    Success or error message

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: list_documents enumerates loaded docs, load_document/remove_document manage the document lifecycle, get_outline provides structure, navigate_section gives context, read_section extracts content, search_document finds text, and get_document_stats offers metadata. An agent can easily differentiate them based on their specific actions and targets.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, such as list_documents, load_document, get_outline, and navigate_section. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming conventions across the eight tools.

Tool Count5/5

With 8 tools, this server is well-scoped for document navigation and analysis, covering core operations like loading, listing, navigating, reading, searching, and removing documents, along with metadata and outline retrieval. Each tool earns its place without redundancy, making the count ideal for the domain.

Completeness5/5

The tool set provides complete CRUD/lifecycle coverage for document navigation: load_document (create), list_documents (read), remove_document (delete), and operations for analysis (get_outline, navigate_section, read_section, search_document, get_document_stats). There are no obvious gaps, ensuring agents can perform all essential tasks without dead ends.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources