Mahesa F. Ferdinand

Corpus Hub contributor since 2026-10-22

Mahesa F. Ferdinand's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

8files

1,326lines

★ 8GitHub stars on repo

Totals across every corpus @Mftrferdinand appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the Zeline-MCP corpus

Mftrferdinand/Zeline-MCP: Curated Model Context Protocol (MCP) servers & connectors designed for Zeline Agentic Framework

Reuse a worked example: the commit “spec-compliant MCP server base, SSRF protection, filesystem san…” (8 files · Python).
Answer from Zeline-MCP's real Python source instead of memory (AI, prompts and agents).

Example questions

What does zeline_mcp do in Zeline-MCP?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository Mftrferdinand/Zeline-MCP with XERJ (https://hub.xerj.org/corpus/mftrferdinand--zeline-mcp).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/Mftrferdinand/Zeline-MCP Zeline-MCP && git -C Zeline-MCP checkout 3dae18a2afc7e0597dac9650294bf3b422978a85
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./Zeline-MCP --url http://127.0.0.1:9200 --prefix zeline-mcp --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus mftrferdinand--zeline-mcp · AI, prompts and agents
Related corpora: camel, jsonformer, huggingface-hub-docs, admission-compare
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 8

Mftrferdinand/Zeline-MCP

3dae18a2af feat: spec-compliant MCP server base, SSRF protection, filesystem san…

selected commit: 8 files · 1,326 lines · Python · zeline_mcp, tests, the project root

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus mftrferdinand--zeline-mcpAIMIT agreed 2026-10-22

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/Mftrferdinand/badge.svg)](https://hub.xerj.org/contributors/Mftrferdinand)

Included with the author's permission (email, 2026-10-22), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.