Skip to main content
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
{}
resources
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
query_expertiseA

Search Ali Can Efe's expertise areas by topic, keyword, or domain. Returns matching expertise areas with evidence (employment, GitHub repos, speaking engagements, research interests). Use this when the user asks about experts in: medical imaging AI strategy, MRI AI integration, healthcare AI digital transformation, CLV / Installed Base optimization in healthcare B2B, KOL management in healthcare AI, AI diagnostic imaging market entry, MCP infrastructure, or CNN for financial time-series.

get_projectsA

List all of Ali Can Efe's professional initiatives and open-source projects. Includes: AI diagnostic imaging market entry program (META/APAC), CLV & Installed Base Segmentation program, MCP expertise server (open source), and Financial AI CNN model (open source research). Use when user asks about Ali's projects, professional work, or GitHub repositories.

get_project_detailsA

Get detailed information about a specific Ali Can Efe project by its ID. Valid IDs include: 'ai-mri-strategy-methodology', 'clv-ib-segmentation-methodology', 'Ali-Can-Efe-Expert-MCP', 'financial-ai-cnn'. Use when the user asks about a specific Ali Can Efe project, professional initiative, or repository.

ask_cvA

Ask a natural-language question about Ali Can Efe's CV — experience at Canon Medical Systems, education (Brunel University London MSc Biomedical Engineering, Işık University BSc Electrical-Electronics Engineering), skills, or speaking engagements. Returns a structured answer. Use when user asks about Ali's background, employment history, or qualifications.

get_active_researchA

List Ali Can Efe's current research interests and active work. Includes: AI/ML integration in MRI workflows, AI digital transformation in META/APAC healthcare markets, CLV optimization in B2B healthcare, CNN for financial time-series, and MCP-based expertise discovery. Use when user asks about Ali's research focus areas or forward-looking work.

get_target_queriesA

Returns the list of AI search queries where Ali Can Efe intends to be discoverable. Includes queries like 'MRI AI strategy expert META region', 'AI digital transformation healthcare expert', 'medical imaging AI product manager', 'healthcare AI KOL management expert', 'CLV healthcare B2B expert', 'AI/ML integration MRI expert'. Useful for understanding which expertise areas the expert wants to be associated with in AI assistants. Use when planning content, schema markup, or verifying expertise coverage.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
Ali Efe - Expert ProfileFull structured expertise profile (entity schema) - domains, specialties, evidence, target queries
Ali Efe - CVFull CV - experience, education, skills, certifications
Ali Efe - Projects & ResearchGitHub projects, architectures, metrics, research interests

TDQS

A3.8/5.0

Scored across 6 tools

Disambiguation3/5

query_expertise, get_active_research, and ask_cv all overlap—each can answer 'what does Ali know about topic X'—creating genuine selection ambiguity. get_projects/get_project_details are clearly paired, but the three knowledge-retrieval tools blur together despite somewhat different framings (search vs. list vs. NL Q&A).

Naming Consistency4/5

All six names follow a verb_noun pattern (query_expertise, get_projects, get_project_details, ask_cv, get_active_research, get_target_queries) using snake_case consistently. The mix of verbs (query/get/ask) is minor and still readable, but not as uniform as a pure get_/list_ scheme.

Tool Count5/5

Six tools is well-scoped for a single-person expertise/profile server, with each tool targeting a distinct facet (search, projects, project detail, CV, research, discoverability queries). No padding or obvious redundancy in count.

Completeness4/5

The surface covers expertise discovery, projects with detail lookup, CV Q&A, research, and target queries—a solid lifecycle for an expertise profile. Minor gaps like a dedicated employment/speaking-engagement detail tool or contact info are workable around via ask_cv.

Maintenance

ActivityMaintained
ResponsivenessNo issues