Academic Proposal MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| WORKSPACE_DIR | No | The workspace directory where proposal files are stored. Used when running the server with Python (e.g., set to ${workspaceFolder} in the MCP client configuration). |
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
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_rubric_checklist_reportC | Menghasilkan laporan audit kepatuhan proposal skripsi dalam format Markdown berdasarkan rubrik evaluasi dan checklist Research Design Canvas (Chapter 1, 2, dan 3). Dapat langsung disimpan ke workspace sebagai berkas Markdown (.md). |
| validate_canvas_complianceA | Memvalidasi kepatuhan naskah proposal terhadap panduan Research Design Model Canvas v2.0. Dapat digunakan untuk segala topik skripsi/tesis. Memeriksa:
|
| get_canvas_guidelinesA | Mengambil rubrik lengkap checklist Research Design Model Canvas v2.0 (LB01-LB06, LR01-LR06, M01-M05) sebagai panduan bagi pengguna atau asisten AI dalam menyusun naskah ilmiah. |
| generate_academic_proposalB | Membuat dokumen DOCX proposal skripsi lengkap berbasis template resmi FILKOM UB. Dapat digunakan oleh mahasiswa mana pun dengan mengisi parameter metadata dan teks bab. |
| inspect_proposal_documentA | Memeriksa struktur dokumen proposal skripsi (.docx) di dalam workspace. Mengembalikan informasi: jumlah paragraf, tabel, seksi, perkiraan kata, dan daftar heading bab/subbab. |
| increment_proposal_versionA | Menduplikasi versi aktif proposal skripsi ke versi baru dan mencatat riwayat perubahan ke version_history.json. Contoh: current_version='v1.0', new_version='v1.1', changelog='Penyelarasan rumusan masalah tunggal' |
| increment_praproposal_versionB | Menduplikasi versi aktif pra-proposal skripsi (.odt) ke versi baru dan mencatat riwayat perubahan ke version_history.json. Contoh: current_version='v1.0', new_version='v1.1', changelog='Penyesuaian rumusan masalah tunggal dan metode riset' |
| export_proposal_as_markdownC | Mengekstraksi seluruh isi dokumen proposal .docx menjadi format Markdown bersih yang mudah dibaca dan diolah oleh LLM / pengguna. |
| plan_proposal_researchC | Menurunkan rumusan masalah tunggal, variabel independen (X), variabel dependen (Y), tujuan penelitian terukur, serta kueri pencarian literatur yang dioptimalkan khusus untuk dijalankan pada MCP paper-search (search_arxiv, search_semantic, search_google_scholar). |
| parse_literature_csv_dataA | Membaca dan mem-parsing berkas CSV literatur penelitian dari workspace (misal: literature.csv). Mengekstrak kolom peneliti, tahun, judul, metode, hasil, dan research gap, serta menghasilkan matriks tabel tinjauan pustaka dan daftar referensi Harvard. |
| generate_proposal_from_topicB | Menghasilkan dokumen proposal skripsi (.docx) lengkap hanya dengan memberikan topik penelitian, data CSV literatur di workspace, dan/atau data paper yang diperoleh dari MCP paper-search. Secara otomatis menyusun Bab 1, Bab 2 (beserta tabel tinjauan pustaka), Bab 3, dan daftar referensi, lalu menyimpannya langsung ke workspace. |
| generate_academic_praproposalA | Membuat berkas Dokumen Pra-Proposal Skripsi (.odt) berbasis template resmi SA2-01A. Menerima metadata mahasiswa dan struktur konten (latar_belakang, landasan_kepustakaan, rumusan_masalah, metode, daftar_pustaka). |
| generate_praproposal_from_topicC | Menghasilkan dokumen pra-proposal skripsi (.odt) SA2-01A secara otomatis dari topik penelitian, data CSV literatur di workspace, dan/atau data paper yang diperoleh dari MCP paper-search. Menyusun Latar Belakang (<= 500 kata), Landasan Kepustakaan (<= 250 kata), Rumusan Masalah (numbering), Metode (<= 250 kata), dan Daftar Pustaka. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| auto_praproposal_workflow | Panduan alur orkestrasi pembuatan pra-proposal skripsi (Form SA2-01A .odt) bagi asisten AI: Mewajibkan konfirmasi data diri mahasiswa/dosen, meneliti literatur, dan menghasilkan naskah pra-proposal. |
| auto_proposal_workflow | Panduan alur orkestrasi otomatis bagi asisten AI (Antigravity): Mewajibkan konfirmasi data diri mahasiswa/dosen, meneliti literatur via paper-search MCP, mengolah CSV, dan menyusun proposal DOCX. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 13 tools
Tools have distinct purposes generally, but some overlap exists between generate_academic_proposal and generate_proposal_from_topic, as both create full proposal DOCX files, differing mainly in input method. Similarly, increment_proposal_version and increment_praproposal_version are distinct by format, so that's fine.
Most tools follow a verb_noun pattern like 'export_proposal_as_markdown', 'generate_academic_proposal', but there is inconsistency: 'validate_canvas_compliance' uses a noun-verb-noun order, and 'generate_rubric_checklist_report' is long and less consistent than others. Also, two tools use different phrasing for similar actions ('increment_proposal_version' vs 'generate_academic_proposal').
With 13 tools, the server is slightly on the heavier side but still within a reasonable range for a comprehensive academic proposal server covering proposal, praproposal, versioning, validation, and literature parsing. Each tool contributes to the workflow, though a few could be merged without loss.
The server covers the main lifecycle: planning (plan_proposal_research), generation (generate_academic_proposal, generate_proposal_from_topic), validation (validate_canvas_compliance), inspection (inspect_proposal_document), versioning (increment_proposal_version), and export (export_proposal_as_markdown). Minor gaps include no explicit tool for updating proposal content after generation or deleting versions, but agents can work around via versioning.