mind-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mind-mcpread the INDEX.md file from .mind"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@modelbound/mind-mcp
An MCP server that exposes a .mind/ folder to any MCP-capable agent (Claude, Cursor, custom).
Tools
Tool | Description |
| Read a |
| Return the routing table from |
| Search memory/context for a query. |
| Create a |
| Score a skill with deterministic trust heuristics (scanner h5) and return confidence trend. |
| List files under a subdirectory of |
Related MCP server: ohmyself
Served skill payload
When reading .mind/skills/*.md, mind_read includes:
version,trust_score,scanner_versionreview_state,review_metaconfidence(pass rate, trust delta, trend)
Field names match the hosted ModelBound product for round-trip compatibility.
Install
npm i -g @modelbound/mind-mcpRun
mind-mcp --root /path/to/projectMigration (0.1 → 0.2)
Skill reads now return JSON payloads for paths under
skills/(not raw markdown only).Add
mind_trustfor explicit trust scoring without a full read.Pair with
@modelbound/mind-clifor review lifecycle (mind review approve,mind review gate).
Security
The server refuses any path that escapes the --root directory. Writes only ever create files under .mind/diff/.
License
Apache 2.0.
Available Tools
5 toolsmind_listB
List markdown files under a subdirectory of .mind/.
| Name | Required | Description | Default |
|---|---|---|---|
| subdir | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It does not specify whether the listing is recursive, what happens if subdir is empty, or the format of the output (e.g., full paths). The behavior is only vaguely described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It does not earn its place fully as it omits important details. It could be expanded with bullet points or additional context without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameter and lack of output schema, the description is incomplete. It does not address output format, recursive behavior, file extension filtering, or error handling. A more complete description would add these details to aid correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must explain the parameter. It mentions 'subdirectory of .mind/' but does not clarify that 'subdir' is a relative path, whether nesting is supported, or the default behavior when omitted. The parameter meaning is ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and the resource (markdown files under a subdirectory of .mind/). It is distinct from sibling tools like mind_read (reading content) and mind_recall (recalling memories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to list markdown files in a subdirectory of .mind/), but provides no explicit conditions, exclusions, or alternatives. The sibling tools have different purposes, so usage context is somewhat clear but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mind_propose_writeC
Create a .mind/diff/*.md proposing a change to a target file.
| Name | Required | Description | Default |
|---|---|---|---|
| reason | No | ||
| target | Yes | ||
| proposal | Yes | ||
| confidence | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it creates a file, but does not disclose behavioral traits such as whether the file is overwritten, required permissions, or side effects. The description is minimal and lacks transparency beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no extra words. However, for a tool with four parameters, it is under-specified and should at least hint at parameter meanings. It earns its place but is not optimally sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should explain return values or side effects, but it does not. The tool is moderately complex (four parameters), yet the description provides no context on what the tool returns, prerequisites, or postconditions. It is completely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides vague context for 'target' (target file) and 'proposal' (proposing a change), but entirely fails to explain 'reason' and 'confidence' parameters. Thus, it adds only partial meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a .mind/diff/*.md file proposing a change to a target file. It identifies the verb 'create' and the resource. The sibling tools (mind_list, mind_read, mind_recall, mind_route) appear to be read/listing operations, so this tool is distinct in function, but the description does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The context of proposing a change is implied but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mind_readB
Read a file inside .mind/ by relative path.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states it reads a file, omitting details like error handling, permissions, or return format. Incomplete for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action and resource, no extraneous information. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal and lacks details on output, errors, or usage scope. For a tool with no output schema and no annotations, this leaves the agent guessing about behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
For the single parameter 'path', the description adds context 'by relative path' which clarifies its meaning beyond the schema. However, it could specify constraints like required format or allowed directory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Read' and the resource 'file inside .mind/' with the method 'by relative path'. This distinguishes it from siblings like mind_list (listing files) or mind_propose_write (writing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to read a file) but provides no guidance on when not to use or alternatives. It could direct to other tools for other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mind_recallB
Search memory/ and context/ files by substring query.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Lacks details on read-only nature, auth requirements, performance, or edge cases like no matches.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, directly states core function. No unnecessary words. Front-loaded with verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one param and no output schema, the description is minimal but covers basic purpose. Missing details on return format and scope could affect selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one param with no description (0% coverage). The description adds that it's a substring query, giving some context, but lacks specifics like case sensitivity or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'Search', the resource 'memory/ and context/ files', and the method 'substring query'. Differentiates from siblings like mind_list or mind_read.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., mind_list, mind_read). No mention of when not to use or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mind_routeA
Return the routing table from INDEX.md.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It indicates a read operation but lacks details about caching, error handling, or source location beyond 'INDEX.md'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. Perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the format of the routing table. While the tool is simple, more detail on what is returned would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. Baseline 4 applies; description adds no extra parameter info but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a specific resource ('routing table') from a specific file ('INDEX.md'). It is distinct from sibling tools like mind_read or mind_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives, but the purpose is straightforward with no parameters. Implied usage is acceptable but could be improved.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
5 tool updates
v0.1.0- First observed
mind_list - First observed
mind_propose_write - First observed
mind_read - First observed
mind_recall - First observed
mind_route
TDQS
Each tool has a clearly distinct purpose: listing, reading, writing proposals, searching, and retrieving routing tables. No overlap or ambiguity.
All tools follow the 'mind_verb' pattern with snake_case, including 'mind_propose_write' which uses a compound verb. The naming is consistent and predictable.
With 5 tools, the set is well-scoped for memory/context management. It covers listing, reading, writing proposals, searching, and routing without being too sparse or excessive.
The set covers core operations but lacks delete or direct update tools. However, the proposal-based workflow may compensate, leaving only minor gaps.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Agent-native MCP server over the public saagarpatel.dev corpus. Read-only, stateless.
Browse and manage files in your Moxt AI workspace from any MCP client.
Your org's AI agents, tasks, runs, search, and brain files as MCP tools and resources.
Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceProvides file system operations (list, read, write, search) via MCP, enabling an AI agent to manage files through natural language.2,013MIT
- AlicenseNot gradedqualityBmaintenanceExposes a personal markdown-based second brain (Obsidian-style) as an MCP server, enabling agents to search, read, and write notes with privacy controls.MIT
- FlicenseNot gradedqualityBmaintenanceMCP server that exposes one or more documentation folders (Markdown, MDX, TXT) to AI agents, enabling listing, reading, and searching of documentation files.-
- AlicenseNot gradedqualityDmaintenanceTurn any folder into a searchable knowledge base for AI, exposed via MCP.1MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ModelBound/mind-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server