Turn your markdown into an MCP.
Make sure you are using Node version 22.
$ mkdir my-mcp.md
$ cd my-mcp.md
$ npx --y mcp.md@latest example -l
$ npm install
$ npx --y mcp.md@latest ingest -l
Use
pwdto get the full MCP path for[pwd]in the next set of instructions.
Add the following configuration to your claude_desktop_config.json.
{
"name": "mcp.md",
"command": "node",
"args": [ "[pwd]/mcp.md.js", "serve", "--cwd", "[pwd]" ]
}
Add the following configuration to your cline_mcp_settings.json.
{
"mcpServers": {
"mcp.md": {
"command": "node",
"args": [ "[pwd]/mcp.md.js", "serve", "--cwd", "[pwd]" ]
}
}
}
Set up the MCP server from https://github.com/cblanquera/mcp.md while adhering to these MCP server installation rules:
- Start by loading the MCP documentation.
- Use "github.com/cblanquera/mcp" as the server name in cline_mcp_settings.json.
- Create the directory for the new MCP server before starting installation.
- Make sure you read the user's existing cline_mcp_settings.json file before editing it with this new mcp, to not overwrite any existing servers.
- Use commands aligned with the user's shell and operating system best practices.
- Once installed, demonstrate the server's capabilities by using one of its tools.
Here is the project's README to help you get started:
All you need to do is configure inputs in config.yml to where your markdown files are actually located and ingest them into your database. The following sections cover the prescribed steps.
The following are the possible configuration options for config.yml.
# MCP Server requires a name (should be slug)
name: "my-mcp"
# MCP Server requires a version
version: 0.0.1
# Add many topics like the following:
inputs:
- topic: coding
# Relative to [pwd]
# Start with / for an exact path
paths: [ "docs/coding/**/*.md" ]
# When there are conflicting rules, the lower rank wins
rank: 10
- topic: documenting
paths: [ "docs/documenting/**/*.md" ]
rank: 20
- topic: testing
paths: [ "docs/testing/**/*.md" ]
rank: 30
# Where to save your database files relative to [pwd]
# Start with / for an exact path
output: "database"
# Batch size of vectors: 64, 128, 256, 512, etc.
batch_size: 64
# If embedding_model is text-embedding-3-small, need to set the below.
openai_host: "https://api.openai.com/v1"
openai_key: "sk-xxx"
# Model to use for embeds: local or text-embedding-3-small
embedding_model: "local"
# Just a provision for later developments
budgets:
max_chunk_tokens: 400
overlap_tokens: 32
The MCP uses Xenova/all-MiniLM-L6-l2 locally to determine the best search query term for the MCP. Think about it like random prompt → correct query → ask MCP. You can upgrade this to use your OpenAI key by adding an openai_host, openai_key and setting embedding_model to text-embedding-3-small in config.yml.
WARNING: OpenRouter doesn't support the
/embeddingsAPI endpoint. This is called when providing an OpenAI compatible host.
Everytime you add or edit new markdown you'll need to update your database like the following.
$ npx --y mcp.md@latest ingest -l
You can manually start the server like the following.
$ npx --y mcp.md@latest serve -l
Create a rule (markdown file) called My-MCP-Rule.md in your knowledge folder (ex. .clinerules) with the following context.
# My MCP Usage Rules
This MCP provides access to knowledge bases and rulesets. Agents must use these tools to ground answers, learn about user-defined code libraries, follow user-defined style guides, and enforce coding or documentation standards.
## 1. General Guidance
- ALWAYS use this MCP to look up knowledge or rules that the user has provided in Markdown.
- NEVER assume defaults: if a topic or tag is unclear, first list available ones.
- PLAN mode → use listing and searching tools to gather relevant context.
- ACT mode → use fetching and enforcement tools to apply style, rules, or examples when producing outputs.
- Prefer **sections over full documents** unless the whole doc is short and necessary.
- ALWAYS cite or enforce rules when producing user-facing drafts.
## 2. Tools & When to Use Them
The following MCP tool sets are used to plan and execute tasks.
### 2.1. Discovery
The following MCP tools are used to discover the overall topics, subjects and sections available.
- **list_topics**
- Use FIRST to learn what high-level topics exist.
- Example: "coding", "testing", "documenting".
- **list_tags**
- Use to discover available tags and their variants.
- Always confirm tag spelling before searching with them.
- **list_documents**
- Use to see which documents exist under a topic or tag filter.
- Use when the user refers to “that style guide document” or similar.
- **list_sections**
- Use to map out a document’s sections before fetching text.
- Use when you need a specific section rather than the whole doc.
### 2.2. Retrieval
The following MCP tools are used to generally retrieve data particulars.
- **search_context**
- Use for general keyword/semantic search across topics.
- Start with `mode=hybrid`. Add `snippet_only=true` for code examples.
- **search_by_tags**
- Use when you know specific tags to require or exclude.
- Strongest option for precision (e.g., `require_tags=["ruleset"]`).
- **fetch_document**
- Use to retrieve full content of a document or specific sections.
- Provide `sections` array when possible to minimize tokens.
- **fetch_section**
- Use to retrieve exact sections by ID, optionally with neighbors.
- Ideal for “show me the context around section X”.
### 2.3. Analysis & Reasoning
The following MCP tools are used to help analyze and rationalize tasks before execution.
- **build_brief**
- Use in PLAN mode to turn a task into a structured brief with references.
- Example: "Write a test plan" → outline + linked ruleset sections.
- **summarize_context**
- Use to compress multiple hits into a summary before acting.
- Helps reduce token load in large docs.
- **compare_context**
- Use to highlight differences between two contexts (e.g., coding vs testing guides).
- **dedupe_context**
- Use to merge overlapping hits before reasoning.
- **expand_context**
- Use when initial search is too narrow and you need neighbors or related sections.
- **list_related**
- Use to find related sections by tags or document proximity.
### 2.4. Governance
The following MCP tools are rule set oriented and must be used during the execution of a task.
- **enforce_rules**
- ALWAYS use in ACT mode before returning final drafts.
- Input is the current draft; output is the applicable rules (MUST, SHOULD, MUST NOT).
- Fix violations before presenting to user.
- **check_rules**
- Use to produce a checklist of rules for a given task.
- Good in PLAN mode when scoping compliance requirements.
- **validate_filters**
- Use to ensure a proposed filter set (tags/topics) actually matches content.
- Run before committing to a narrow search.
### 2.5. Output & Support
The following MCP tools are available for general support for both planning and executing tasks.
- **cite_context**
- Use to convert section IDs into stable citation metadata.
- ALWAYS attach citations when you rely on context.
- **extract_code**
- Use to pull fenced code blocks only, not prose.
- Ideal for examples, snippets, or test templates.
- **export_context**
- Use to package selected context for reuse or external reporting.
## 3. Mandatory Practices
- MUST check `list_topics` or `list_tags` before attempting a narrow search if the scope is ambiguous.
- MUST call `enforce_rules` before returning any draft that involves formatting, style, or coding standards.
- MUST use `cite_context` when referencing any guidance from this MCP in the final answer.
- SHOULD prefer `search_by_tags` over `search_context` when a relevant tag is known.
- SHOULD use `summarize_context` when multiple hits are too verbose to include raw.
- MAY expand context (`expand_context` or `list_related`) if search results appear incomplete.
FAQs
Turn your markdown into an MCP
The npm package mcp.md receives a total of 0 weekly downloads. As such, mcp.md popularity was classified as not popular.
We found that mcp.md demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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