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Glama

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

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_academic_papersA

Search peer-reviewed papers and preprints across arXiv and Semantic Scholar. Returns sanitized paper abstracts with publication years, citation counts, and authors.

fetch_paper_deep_contextA

Fetch structured, sanitized abstract and detailed technical context for a specific arXiv ID. Normalizes LaTeX equations and neutralizes any prompt injection payloads.

search_repo_implementationsB

Search verified open-source GitHub repositories for code implementations and architectural patterns. Strips license boilerplate and formats clean implementation snippets.

fallback_web_searchB

Zero-cost DuckDuckGo search fallback for recent news, product launches, and general topics. Applies anti-poisoning filter to all retrieved snippets.

match_tools_for_queryB

RAG over Tool Capabilities: Evaluates semantic capability fit to pick ONLY necessary tools, pruning irrelevant tools to prevent token bloat and context overload.

unified_research_contextA

End-to-end multi-source research context pipeline with Tool Capability RAG & Token Budgeting.

  1. RAG-selects ONLY the top 1-2 optimal tools based on semantic capability match.

  2. Prunes unneeded tools to prevent API waste and context overload.

  3. Sanitizes all retrieved snippets and removes prompt injection payloads.

  4. Cross-encoder reranks on CPU and returns bounded, dense grounded context.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 6 tools

Disambiguation3/5

The source-specific search tools are clearly distinct, but match_tools_for_query and unified_research_context both describe RAG-based tool selection and pruning, creating overlap in purpose. unified_research_context also partially subsumes the direct search tools, so boundaries are not fully clean.

Naming Consistency3/5

Most names use lower_snake_case and a search/fetch style, but the convention is inconsistent: fallback_web_search and unified_research_context are noun/adjective phrases rather than verb-first names. match_tools_for_query adds a prepositional construct, so the set doesn't follow a single predictable pattern.

Tool Count4/5

Six tools is a reasonable size for a multi-source research server. However, the set is slightly redundant because match_tools_for_query duplicates part of unified_research_context's functionality, so not every tool is strictly necessary.

Completeness4/5

The server covers academic search, deep paper context, code repository search, web fallback, and an end-to-end pipeline, which is solid for its stated purpose. Minor gaps remain, such as fetching papers by DOI or Semantic Scholar ID, but they are not blocking for typical research workflows.

Maintenance

ActivityMaintained
ResponsivenessNo issues