atlassian-readonly
This MCP server provides read-only Jira and Confluence retrieval and search capabilities.
Read a single Jira issue by issue key, with optional JMESPath projection.
Search Jira using JQL (bounded results, limit 1–50) with optional projection.
Read a Confluence page by numeric page ID, converting storage HTML to Markdown, with optional projection.
Search Confluence using CQL (bounded results, limit 1–50) with optional projection.
It has no write operations.
Provides read-only access to Confluence Cloud, allowing users to read pages and search using CQL.
Provides read-only access to Jira Cloud, allowing users to retrieve issues and search using JQL.
Click on "Deploy 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., "@atlassian-readonlySearch Jira for open bugs assigned to me and summarize them."
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.
Atlassian Read-only
Read-only Jira and Confluence toolkit for AI agents — no write operations are possible.
📋 Table of Contents
Related MCP server: MCP Atlassian Server
Features
Capability | Jira | Confluence |
Read a single issue/page | ✅ | ✅ |
Search with query language | ✅ JQL | ✅ CQL |
Projections (JMESPath subset) | ✅ | ✅ |
Any allowlisted read endpoint | ✅ | ✅ |
Response size limits | ✅ | ✅ |
Secret redaction | ✅ | ✅ |
HTML→Markdown conversion | — | ✅ optional dependency |
Read-only by construction — only GET, allowlisted paths, no POST/PUT/PATCH/DELETE.
Three Ways to Use
Method | Best for | Setup |
Agent Skill | Casual queries via Claude/Copilot |
|
MCP Server | Persistent tool integration in VS Code, CLI, Claude Code | Config file |
Direct Script | Scripts, CI, token-efficient calls |
|
Quick Start
1. Install the skill
npx skills add AlexSchaap-TMMC/atlassian-readonly --skill atlassian-readonlyThe --skill argument is required because the GitHub repository may contain multiple skills (multiple directories under skills/). This flag tells the installer which skill directory to install. Without it, the installer wouldn't know which of potentially many skills to use.
2. Run setup
cd ~/.agents/skills/atlassian-readonly
npm run setupThat single command stores your credentials in the OS credential store (Windows
Credential Manager, macOS Keychain, or Linux Secret Service; falling back to
~/.config token files where none exists), enables the corporate certificate store
if it detects TLS inspection, and verifies both tokens against the live API.
Nothing is installed first: the scripts use Node built-ins only, so the skill works
straight after step 1. Non-interactive:
npm run setup -- "you@example.com" "<jira-token>" "<confluence-token>"Token creation and scope requirements are in skills/references/setup.md; the same file covers rotation, headless/WSL setups, and troubleshooting.
3. Ask your agent
Read HEC-123 and summarize its acceptance criteria.
Search Jira for open bugs assigned to me.
Search Confluence for pages about Kafka retry handling.💡 Finding space keys: When searching Confluence, use the space key (not display name). Run
node ./skills/atlassian.mjs confluence search --cql 'title ~ "project-name"'first to discover the correct space key from results.
Direct Script Execution
For fast, token-efficient access, run the bundled script directly:
💡 Corporate networks: Prepend
NODE_OPTIONS="--use-system-ca"for Zscaler/corporate TLS.
# Read a Jira issue
node ./skills/atlassian.mjs jira get-issue --issue-key HEC-123
# Search Jira with JQL
node ./skills/atlassian.mjs jira search-issues --jql 'project=HEC AND status="To Do"' --limit 10
# Read a Confluence page
node ./skills/atlassian.mjs confluence get-page --page-id 123456789
# Search Confluence with CQL
node ./skills/atlassian.mjs confluence search --cql 'title ~ "Kafka"' --limit 10For an "open" filter use status, not statusCategory: statusCategory=Open returns 0
issues on this tenant. See
troubleshooting.
Projections
Reduce response size with --projection (a JMESPath subset, no dependency needed):
node ./skills/atlassian.mjs jira search-issues \
--jql 'project=HEC' \
--projection 'issues[*].{key: key, summary: fields.summary, status: fields.status.name}'
node ./skills/atlassian.mjs confluence get-page \
--page-id 123 \
--projection 'title,body[storage].value'JMESPath object shorthand {key, summary} is invalid — object entries need explicit
name: expression pairs, and nested fields must use their full path. Supported syntax is
a.b.c, [0], [-1], ["key"], [*], {k: expr}, |, @ and length(); filters,
slices and other functions are rejected with an explicit error.
Any Other Read Endpoint
Use get for allowlisted GET paths the named commands do not cover:
node ./skills/atlassian.mjs jira get \
--path '/rest/api/3/issue/HEC-123/changelog' --projection 'values[*].id'
node ./skills/atlassian.mjs confluence get \
--path '/wiki/api/v2/pages' --query 'limit=5&sort=-created-date' --projection 'results[*].{t: title}'Validate Tokens
Check tokens before API calls to avoid wasted requests:
node ./skills/atlassian.mjs test jira # exit 0 = valid, exit 1 = invalid
node ./skills/atlassian.mjs test confluenceMCP Server
The bundled server exposes four tools via stdio:
Tool ID | Description |
| Read a single Jira issue |
| Search Jira with JQL |
| Read a Confluence page |
| Search Confluence with CQL |
GitHub Copilot in VS Code
Run MCP: Open User Configuration from the Command Palette, then add:
{
"servers": {
"atlassian-readonly": {
"type": "stdio",
"command": "node",
"args": ["./skills/server.mjs"],
"env": {
"ATLASSIAN_USER_EMAIL": "your.email@example.com",
"NODE_OPTIONS": "--use-system-ca"
}
}
}
}Reload VS Code, open Copilot Chat, select Configure Tools, and enable the four Atlassian tools.
GitHub Copilot CLI
copilot mcp add atlassian-readonly \
--env ATLASSIAN_USER_EMAIL="your.atlassian.email@example.com" \
--env NODE_OPTIONS="--use-system-ca" \
-- node ./skills/server.mjsClaude Code
Edit ~/.claude/mcp.json:
{
"servers": {
"atlassian-readonly": {
"command": "node",
"args": ["./skills/server.mjs"],
"env": {
"ATLASSIAN_USER_EMAIL": "your.email@example.com",
"NODE_OPTIONS": "--use-system-ca"
}
}
}
}Manual mcp.json
cp ./skills/references/mcp.json atlassian-readonly-mcp.jsonThen update args to the absolute path of skills/server.mjs and set
ATLASSIAN_USER_EMAIL. Load it into your client as mcpServers — the file holds one
server object, not the whole mcpServers map.
Create API Tokens
Open Atlassian API tokens and create two separate tokens (Jira and Confluence cannot share one).
Jira token
read:jira-workThis classic scope alone is verified for issue retrieval and JQL search. Atlassian rejects granular Jira scopes with 401 Unauthorized; scope does not match.
Confluence token
read:page:confluence
read:content-details:confluence
search:confluenceThese granular scopes are verified for CQL search and full page retrieval.
⚠️ Scopes are fixed at creation time. Copy each token immediately — the dialog won't show it again. Never place tokens in source files, config, shell history, issues, or chat.
Store & Rotate Credentials
npm run setup stores credentials for you. To rotate or remove them afterwards:
npm run configure -- jira # replace
npm run configure -- confluence # replace
npm run configure -- jira delete # remove
npm run configure -- confluence deleteTokens are saved in your OS credential store (Windows Credential Manager, macOS Keychain,
or Linux Secret Service), falling back to ~/.config/atlassian-<product>-token with mode
0600 where no credential store is reachable.
⚠️ Local deletion does not revoke the token at Atlassian. Revoke it separately from Atlassian's token management page.
Troubleshooting
See skills/references/setup.md for the full list, including why a valid token can be reported as invalid and how to confirm which credential source each product resolves from.
Corporate certificates (Zscaler, etc.)
TLS inspection re-signs HTTPS traffic with a corporate CA. npm run setup detects this
and records it in the git-ignored config.json; force it with npm run setup -- --system-ca. Alternatively set NODE_OPTIONS=--use-system-ca (supported Node.js
versions).
Or export the non-expired corporate CA as Base-64 PEM and set NODE_EXTRA_CA_CERTS to its path. Never disable TLS verification.
WSL
WSL uses a separate Linux trust store. Export the corporate root and intermediate certificates from Windows, save as .crt, then:
sudo cp *.crt /usr/local/share/ca-certificates/
sudo update-ca-certificatesRestart WSL before retrying HTTPS clients.
WSL & Headless Systems
npm run setup writes ~/.config/atlassian-<product>-token files (mode 0600) when no
device credential store is reachable — no manual steps needed. To place them by hand:
mkdir -p ~/.config
install -m 600 /dev/null ~/.config/atlassian-user-email
install -m 600 /dev/null ~/.config/atlassian-jira-token
install -m 600 /dev/null ~/.config/atlassian-confluence-token
printf '%s' "your.email@example.com" > ~/.config/atlassian-user-email
read -rsp "Jira API token: " token; echo
printf '%s' "$token" > ~/.config/atlassian-jira-token
read -rsp "Confluence API token: " token; echo
printf '%s' "$token" > ~/.config/atlassian-confluence-token
unset tokenOr set environment variables:
export ATLASSIAN_USER_EMAIL_FILE=~/.config/atlassian-user-email
export ATLASSIAN_JIRA_TOKEN_FILE=~/.config/atlassian-jira-token
export ATLASSIAN_CONFLUENCE_TOKEN_FILE=~/.config/atlassian-confluence-tokenATLASSIAN_<PRODUCT>_API_TOKEN is read at a higher priority than the credential
store, which is what you want in CI. Keep it process-scoped and never persist it in
desktop configuration.
Repository Layout
skills/
SKILL.md agent-facing instructions (kept short)
references/setup.md detailed setup and troubleshooting
setup.mjs one-command setup + verification
atlassian.mjs CLI and the read-only operations
jmespath.mjs projection evaluator (no dependencies)
server.mjs MCP stdio server (needs npm install)
credentials.mjs credential resolution + config.json TLS
wincred.mjs Windows Credential Manager reads, no dependencies
configure.mjs interactive rotate/remove
save-keyring-tokens.mjs
scripts/check-tokens.sh credential-store-free validator (curl)
scripts/run.sh TLS wrapper for atlassian.mjs
scripts/unpin-tokens.sh drop token-file pins from config.json
test/ node:test suites
DEPENDENCIES.md why the core has zero dependencies, and how to keep it that waynpm run check syntax-checks every entry point; npm test runs the unit tests; npm run setup -- --check verifies live credentials without changing anything.
Security
Defense in depth
┌─────────────────────────────────────────────────────┐
│ YOUR REQUEST │
└──────────────┬──────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────┐
│ Layer 2: Implementation Enforcement │
│ • GET only, paths restricted to an allowlist │
│ • No custom host or method │
│ • Response size-limited, secrets redacted │
└──────────────┬──────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────┐
│ Layer 1: Token Scopes │
│ • Jira: read:jira-work │
│ • Confluence: read:page, read:content-details, │
│ search:confluence │
│ • Atlassian rejects any write attempt │
└─────────────────────────────────────────────────────┘Key guarantees:
No writes possible — neither Atlassian nor this code allows write operations.
Allowlisted paths —
--pathaccepts only/rest/api/3/...and/wiki/...GETs.Bounded responses — size limits prevent excessive data exfiltration.
Secret redaction — common credential patterns are masked in output.
Visibility inherited — the runtime can only read content the token account can already access.
⚠️ Supplying a broader token weakens the token layer but does not enable write operations in this code.
See SECURITY.md for vulnerability reporting guidelines.
License
⚠️ Internal Use Only — This software was developed on Toyota hardware during Toyota work hours. It is intended for use by Toyota employees only.
TODO: Confirm the correct license and copyright holder with Toyota's internal IP/Legal team. The current LICENSE file may need updating.
Available Tools
4 toolsconfluence_get_pageA
Read a Confluence page by ID and convert storage HTML to Markdown. This server has no write operations.
| Name | Required | Description | Default |
|---|---|---|---|
| page_id | Yes | ||
| projection | No | Optional JMESPath projection to reduce returned fields. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It discloses the conversion behavior (storage HTML to Markdown) and states the server has no write operations, which is helpful. However, it does not mention error handling, response format, or any limits, leaving gaps for an agent.
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?
Two sentences, no filler. The main purpose is front-loaded, and the read-only clarification is concise and useful. Every word earns its place.
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 read tool with only two parameters and no output schema, the description covers the core purpose and behavioral nuance. It does not explain return structure or error scenarios, but these are less critical given the tool's simplicity. Overall, it is sufficiently complete for an agent to call it correctly.
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 coverage is 50%: projection has a description, but page_id does not. The description does not compensate for the missing page_id semantics beyond reiterating 'by ID'. It adds nothing about projection beyond the schema, so minimal value is provided for parameters.
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 states a clear verb ('Read') and a specific resource ('Confluence page by ID'), plus a distinctive detail (conversion to Markdown). This distinguishes it from sibling tools like confluence_search and jira_get_issue without needing to inspect the schema.
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 clearly implies usage when a page ID is known, but it does not explicitly contrast with confluence_search or state when NOT to use this tool. The read-only note provides general context, but no alternative routing guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
confluence_searchA
Search Confluence with CQL. Results are bounded; this server has no write operations.
| Name | Required | Description | Default |
|---|---|---|---|
| cql | Yes | ||
| limit | No | ||
| projection | No | Optional JMESPath projection to reduce returned fields. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It adds useful context by stating 'Results are bounded' and 'this server has no write operations,' which helps the agent understand output scaling and that the tool performs no mutations. It does not detail result shape or error behavior, but for a simple search tool this is reasonably transparent.
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 two sentences, front-loaded with the core purpose, and contains no filler. The safety note about no write operations is brief and earns its place given the lack of annotations.
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 three-parameter search tool, the description plus schema covers the basic calling contract, but there is no output schema and the description does not mention what the search returns, pagination behavior, or any example CQL. 'Results are bounded' hints at limits but leaves practical expectations underspecified.
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 only 33% because only projection has a description. The main description mentions CQL, which gives some meaning to the cql parameter, but it does not explain how to construct CQL, what limit controls beyond its schema constraints, or how projection interacts with results. The description does not sufficiently compensate for the low schema coverage.
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 states a specific action and resource: 'Search Confluence with CQL.' This clearly separates it from sibling tools like jira_search_issues and confluence_get_page, since the resource (Confluence) and operation (search) are both explicit.
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 this tool should be used for searching Confluence, but it does not explicitly say when to choose it over siblings such as confluence_get_page or jira_search_issues. There is no when-not-to-use guidance or mention of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
jira_get_issueA
Read one Jira issue. This server has no write operations.
| Name | Required | Description | Default |
|---|---|---|---|
| issue_key | Yes | ||
| projection | No | Optional JMESPath projection to reduce returned fields. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It does mention the read-only nature and that the server has no write operations, which is useful context. However, it does not describe error behavior, response format, or what happens when the issue does not exist.
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 two short sentences, both earning their place. It front-loads the core action and adds the server-wide write constraint without any redundant phrasing.
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 read tool, the inputs and general action are covered, but the absence of an output schema means the return value is only implied. The description does not clarify what fields are returned or how to interpret the response, leaving a moderate gap for the agent.
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?
The schema provides a pattern for issue_key and a description for projection, but the tool description itself adds no parameter-level explanation. With schema coverage at 50%, the description does not compensate for the undocumented issue_key semantics, though the parameter name is fairly self-explanatory.
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 states a specific verb ('read') and resource ('one Jira issue'), making the tool's purpose unmistakable. It is clearly differentiated from sibling search and Confluence tools by focusing on a single issue retrieval.
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 usage when a specific issue key is available, but it does not explicitly mention jira_search_issues as the alternative for query-based retrieval. There is no warning against using it for searches or a clear when-not-to-use statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
jira_search_issuesB
Search Jira with JQL. Results and fields are bounded; this server has no write operations.
| Name | Required | Description | Default |
|---|---|---|---|
| jql | Yes | ||
| limit | No | ||
| projection | No | Optional JMESPath projection to reduce returned fields. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It adds two useful traits: 'Results and fields are bounded' and 'this server has no write operations', which are not present in the schema. However, it omits details like pagination, ordering, rate limits, or error behavior, so transparency is partial.
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, tight sentence that front-loads the core action and immediately adds a scope limitation. No filler words or redundant repetition of the tool name. Every phrase contributes meaning.
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 three parameters, no output schema, and no annotations, the description is not sufficient. It does not describe what a search result looks like, how to construct a valid JQL query, or the effect of 'limit' and 'projection'. The bounded/no-write note is useful but only addresses safety, not 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?
Only 33% of the parameters have schema descriptions (projection). The description clarifies that 'jql' is the Jira Query Language string, but it does not explain the 'limit' parameter or add syntax/format details. Since schema coverage is low, the description should compensate more but does not for two of the three parameters.
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 names a specific verb ('Search') and resource ('Jira'), and correctly implies searching issues via the tool name and JQL mention. It distinguishes from jira_get_issue (which fetches a single issue) and confluence_search (different product), though it does not explicitly say 'issues' or contrast these siblings.
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 versus alternatives. The description does not mention jira_get_issue, confluence_search, or any condition that would select one over the other. The only usage hint is 'Search Jira with JQL', which is implied functionality rather than a directive.
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.
4 tool updates
v0.1.0- First observed
confluence_get_page - First observed
confluence_search - First observed
jira_get_issue - First observed
jira_search_issues
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: get versus search for both Jira and Confluence. There is no overlap or ambiguity between any pair, enabling precise tool selection.
All tool names follow a consistent product_action pattern with snake_case (e.g., jira_get_issue, confluence_search). The naming is uniform and predictable.
With 4 tools covering two products (Jira and Confluence) each having a get and search operation, the count is well-scoped for a read-only server. No tool feels redundant or missing.
The read-only surface provides essential get and search for both products. Minor gaps exist such as bulk fetch or additional metadata endpoints, but core querying needs are well covered.
Maintenance
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